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2024



【ACMMM 2022】Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors


【ICLR 2022】LoRA:Low-Rank Adaptation of Large Language Models


【ICCV 2023】RQ-LLIE:Low-Light Image Enhancement with Multi-stage Residue Quantization and Brightness-aware Attention


【CVPR 2018】SID:Learning to See in the Dark


【ICML 2018】Laplace Pyramid Loss:Optimizing the Latent Space of Generative Networks


【ECCV 2022】FECNet:Deep Fourier-based Exposure Correction Network with Spatial-Frequency Interaction


【ICCV 2023】Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising


【TIP 2021】Fast Hyperspectral Image Recovery of Dual-Camera Compressive Hyperspectral Imaging via Non-Iterative Subspace-Based Fusion


【TPAMI 2023】PIDS:Prior Image Guided Snapshot Compressive Spectral Imaging


【 ICCV 2023】Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction


【WACV 2024】Beyond RGB: A Real World Dataset for Multispectral Imaging in Mobile Devices


【NIPS 2022】Deep fourier up-sampling


【arXiv 2023】SpectralGPT:Spectral Foundation Model


【ICCV 2023】MRLPFNet:Multi-scale Residual Low-Pass Filter Network for Image Deblurring


【NIPS 2022】SatMAE:Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery


【NIPS 2023】Hyper-Skin: A Hyperspectral Dataset for Reconstructing Facial Skin-Spectra from RGB Images


【NIPS 2022】ScaoedNet:Enhanced Latent Space Blind Model for Real Image Denoising via Alternative Optimization


2023

【arXiv 2023】UEM:Computational Spectral Imaging with Unified Encoding Model: A Comparative Study and Beyond


【arXiv 2023】In2SET: Intra-Inter Similarity Exploiting Transformer for Dual-Camera Compressive Hyperspectral Imaging


【WACV 2024】Beyond Fusion:Modality Hallucination-based Multispectral Fusion for Pedestrian Detection


【CVPR 2022】Explore Spatio-temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline


【ICCV 2023】DreamTeacher:Pretraining Image Backbones with Deep Generative Models


【CVPR 2023】MobileOne: An Improved One millisecond Mobile Backbone


【ICCV 2023】DAT:Dual Aggregation Transformer for Image Super-Resolution


【TMM 2023】DADF-Net:Degradation-aware Dynamic Fourier-based Network For Spectral Compressive Imaging


【ICML 2022】RETRO:Improving language models by retrieving from trillions of tokens


【NIPS 2022】CAT:Cross Aggregation Transformer for Image Restoration


【ICML 2020】REALM: Retrieval-Augmented Language Model Pre-Training


【arXiv 2023】RCG:Self-conditioned Image Generation via Generating Representations


【arXiv 2023】SINR:Spectral-wise Implicit Neural Representation for Hyperspectral Image Reconstruction


【Arixiv 2023】Benchmarking Large Language Models in Retrieval-Augmented Generation


【JSTSP 2021】MoG-DUN:Accurate and Lightweight Image Super-Resolution With Model-Guided Deep Unfolding Network


【TGRS 2023】NLSSR:Nonlocal Structured Sparsity Regularization Modeling for Hyperspectral Image Denoising


【CVPRW 2022】SSHOD:Semi-Supervised Hyperspectral Object Detection Challenge Results - PBVS 2022


【TIP 2023】Spatially Varying Prior Learning for Blind Hyperspectral Image Fusion


【EMNLP 2023】Is the Answer in the Text? Challenging ChatGPT with Evidence Retrieval from Instructive Text


【TPAMI 2023】DGSMP:Deep Gaussian Scale Mixture Prior for Image Reconstruction


【TCSVT 2019】Fast Parallel Implementation of Dual-Camera Compressive Hyperspectral Imaging System


【CVPR 2023】Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising


【NIPS 2020】RAG:Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks


【Research & Writting】TCSVT 投稿


【CVPR 2023】Zero-Shot Noise2Noise:Efficient Image Denoising without any Data


【Research & Writing】Remote Sensing 投稿


【CVPR 2023】CABM:Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large Input


【Research & Writing】期刊选择


【CVPR 2023】ETDS:Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-Resolution


【CVPR 2023】OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer


【ICCV 2023】DLGSANet: Lightweight Dynamic Local and Global Self-Attention Network for Image Super-Resolution


【ICCV 2023】RC-LUT:Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution


【深度学习】LVM:Sequential Modeling Enables Scalable Learning for Large Vision Models


【ICCV 2023】DARSR:Learning Correction Filter via Degradation-Adaptive Regression for Blind Single Image Super-Resolution


【ICCV 2023】DCD-Net:Iterative Denoiser and Noise Estimator for Self-Supervised Image Denoising


【ICCV 2023】SRFormer: Permuted Self-Attention for Single Image Super-Resolution


【ICCV 2023】SPIN:Lightweight Image Super-Resolution with Superpixel Token Interaction


【ICCV 2023】VQD-SR:Learning Data-Driven Vector-Quantized Degradation Model for Animation Video Super-Resolution


【深度学习】LangChain


【ICCV 2023】CTM-SCI:Unfolding Framework with Prior of Convolution-Transformer Mixture and Uncertainty Estimation for Video Snapshot Compressive Imaging


【ICCV 2023】The Devil is in the Upsampling:Architectural Decisions Made Simpler for Denoising with Deep Image Prior


【CVPRW 2023】Quadformer:Vision Transformers with Mixed-Resolution Tokenization


【TPAMI 2023】What Makes for Good Tokenizers in Vision Transformer?


【CVPR 2023】MaskedDenoising:Masked Image Training for Generalizable Deep Image Denoising


【CVPR 2023】SRNO:Super-Resolution Neural Operator


【ACL 2023】AAR:Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In


【CVPR 2023】NGramSwin:N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution


【CVPR 2023】DAEM:Toward Stable, Interpretable, and Lightweight Hyperspectral Super-resolution


【CVPR 2023】SUDF:Spectral Bayesian Uncertainty for Image Super-resolution


【CVPR 2023】GMT-Net:Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement


【CVPR 2023】Burstormer: Burst Image Restoration and Enhancement Transformer


【深度学习】GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints


【深度学习】基于 LLM 构建中文场景检索式对话:Llama2+NeMo


【Research & Writing】CVPR 2024 注意事项


【机器学习】Single-shot compressive spectral imaging with a dual-disperser architecture


【Research & Writing】markdown 小书匠配置


【深度学习】DLTR:Computational Hyperspectral Imaging Based on Dimension-discriminative Low-rank Tensor Recovery


【深度学习】Hyperspectral Image Reconstruction using Deep External and Internal Learning


【深度学习】Progressive Distillation for Fast Sampling of Diffusion Models


【深度学习】AAAI2024


【深度学习】Denoising Diffusion Models for Plug-and-Play Image Restoration


【深度学习】Diffusion models as plug-and-play priors


【机器学习】NCSR:Nonlocally Centralized Sparse Representation for Image Restoration


【机器学习】NL-means:A non-local algorithm for image denoising


【深度学习】MAE_ST:Masked Autoencoders As Spatiotemporal Learners


【深度学习】DPIR:Plug-and-Play Image Restoration with Deep Denoiser Prior


【深度学习】Consistency Models


【深度学习】DDS2M:Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restoration


【深度学习】Deep Unfolding, Diffusion Model and CASSI


【深度学习】ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI


【Geek】树莓派开发日记


【Research & Writing】CVPR 2023 Presenter and Virtual Platform Upload REMINDER


【深度学习】Converting a spectrum to a colour


【Geek】绑定 XDU 邮箱到 iOS


【深度学习】注册机制不能很好地扩展


【Research & Writing】NTU School of EEE Request for Approval to Host Non-Graduating(NG) Research Student


【Research & Writing】2023 China Scholarship Council (CSC) 注意事项


【深度学习】No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning


【深度学习】Lazy Configs


【深度学习】GDP:Generative Diffusion Prior for Unified Image Restoration and Enhancement


【深度学习】MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detection


【深度学习】SERT:Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising


【Research & Writing】How to write Statement of Purpose (SOP)


【深度学习】DR2:Diffusion-based Robust Degradation Remover for Blind Face Restoration


【深度学习】Learning to Generate Data by Estimating Gradients of the Data Distribution


【深度学习】Maximum Likelihood Training of Score-Based Diffusion Models


【深度学习】Score-based diffusion models for accelerated MRI


【深度学习】Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction


【深度学习】SNIPS: Solving Noisy Inverse Problems Stochastically


【Research & Writing】Instructions for Validation and Final Submission of CVPR 2023 Camera-Ready Papers


【Research & Writing】加拿大签证


【深度学习】2023 NTIRE NH Dehazing Factsheet


【Research & Writing】 CVPR 2023 注册


【深度学习】Palette: Image-to-Image Diffusion Models


【Research & Competition】CVPR2023 Workshop 竞赛汇总


【深度学习】DDIM:Denoising Diffusion Implicit Models


【深度学习】Taming Transformers for High-Resolution Image Synthesis


【深度学习】IR-SDE: Image Restoration with Mean-Reverting Stochastic Differential Equations


【深度学习】Three Ways of Storing and Accessing Lots of Images in Python


【深度学习】A Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble Learning


【深度学习】NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images


【深度学习】IM2ELEVATION: Building Height Estimation from Single-View Aerial Imagery


【深度学习】Detectron2 代码解读


【深度学习】CenterMask : Real-Time Anchor-Free Instance Segmentation


【深度学习】MMdet 代码解读


【深度学习】Understanding Diffusion Models: A Unified Perspective


【深度学习】Robust Compressed Sensing MRI with Deep Generative Priors


【深度学习】Sovling Inverse Problems in Medical Imaging with Score-Based Generative Models


【深度学习】Generative Modeling by Estimating Gradients of the Data Distribution


【深度学习】What are Diffusion Models?


2022

【深度学习】Hungarian loss:End-to-end people detection in crowded scenes


【深度学习】Plug-and-Play Image Restoration with Deep Denoiser Prior


【深度学习】Stable Diffusion:High-Resolution Image Synthesis with Latent Diffusion Models


【深度学习】PointPillars: Fast Encoders for Object Detection from Point Clouds


【深度学习】SECOND: Sparsely Embedded Convolutional Detection


【深度学习】Score-baed Diffusion:Score-Based Generative Moddling Through Stochastic Differential Equations


【深度学习】Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite


【深度学习】VoxelNet:End-to-End Learning for Point Cloud Based 3D Object Detection


【深度学习】DAIR-V2X Project


【深度学习】DDRM:Denoising Diffusion Restoration Models


【深度学习】Deblurring via Stochastic Refinement


【深度学习】OFA:Unifying Architectures, Tasks, and Modalities through a Simple Sequence-to-Sequence Learning Framework


【深度学习】Real-Time Object Detection and Localization in Cimpressive Sensed Video


【深度学习】Video object detection from one single image through opto-electronic neural network


【深度学习】COCO Datasets


【深度学习】Diffusion Model


【深度学习】Diffusion Model:Deep Unsupervised Learning using Nonequilibrium Thermodynamics


【深度学习】ATSS:Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection


【深度学习】DDPM:Denoising Diffusion Probabilistic Models


【机器学习】Generalized Assorted Pixel Camera(CAVE):Postcapture Control of Resolution, Dynamic Range, and Spectrum


【机器学习】Harvard:Statistics of Real-World Hyperspectral Images


【深度学习】ICVL:Sparse Recovery of Hyperspectral Signal from Natural RGB Images


【深度学习】光谱图像数据集合集


【深度学习】From compressive sampling to compressive tasking: retrieving semantics in compressed domain with low bandwidth


【深度学习】ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection


【深度学习】DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection


【Geek之路】Programing Enhancement Proposals


【深度学习】Fast R-CNN


【深度学习】DiffusionDet: Diffusion Model for Object Detection


【深度学习】OHEM:Training Region-based Object Detectors with Online Hard Example Mining


【机器学习】FISTA:A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems


【Research & Writing】上传arXiv


【深度学习】DPM-SOLVER++: Fast Solver for Guided Sampling of Diffusion Problistic Models


【深度学习】DPM-Solver:A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps


【深度学习】DCN:Deformable Convolutional Networks


【深度学习】Deformable ConvNets v2: More Deformable, Better Results


【深度学习】S2-TRANSFORMER FOR MASK-AWARE HYPERSPEC- TRAL IMAGE RECONSTRUCTION


【深度学习】Mask R-CNN


【深度学习】RetinaNet:Focal Loss for Dense Object Detection


【深度学习】SOLOv2: Dynamic and Fast Instance Segmentation


【深度学习】SOLO: Segmenting Objects by Locations


【深度学习】OTA: Optimal Transport Assignment for Object Detection


【深度学习】DINO:DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection


【深度学习】Conditional DETR for Fast Training Convergence


【深度学习】DESTR: Object Detection with Split Transformer


【深度学习】FCOS: Fully Convolutional One-Stage Object Detection


【深度学习】ViTDet:Exploring Plain Vision Transformer Backbones for Object Detection


【深度学习】3DT-Net :Learning A 3D-CNN and Transformer Prior for Hyperspectral Image Super-Resolution


【深度学习】USRNet:Deep Unfolding Network for Image Super-Resolution


【Research & Writting】OpenReview 投稿


【深度学习】压缩光谱成像系统中物理实现架构研究综述


【深度学习】BEVFormer++:Improving BEVFormer for 3D Camera-only Object Detection:1st Place Solution for Waymo Open Dataset Challenge 2022


【深度学习】BEVFormer:Learning Bird’s-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers


【Research】CVPR 2023 Call for Papers


【深度学习】Libra R-CNN:Towards Balanced Learning for Object Detection


【深度学习】YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors


【深度学习】CSPNet:A New Backbone That Can Enhance Learning Capability of CNN


【深度学习】DETR:End-to-End Object Detection with Transformers


【深度学习】Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer


【深度学习】BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation


【深度学习】Spatial as Deep(SCNN): Spatial CNN for Traffic Scene Understanding


【深度学习】YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications


【深度学习】YSLAO: You Should Look at All Objects


【深度学习】FPN:Feature Pyramid Networks for Object Detection


【深度学习】YOLOv3: An Incremental Improvement


【深度学习】EfficientDet: Scalable and Efficient Object Detection


【深度学习】PANet:Path Aggregation Network for Instance Segmentation


【Research & Writing】Matlab 使用方法记录


【深度学习】SFNet:Semantic Flow for Fast and Accurate Scene Parsing


【深度学习】DeepLab V3:Rethinking Atrous Convolution for Semantic Image Segmentation


【深度学习】DeepLab:Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs


【深度学习】DeSCI:Rank Minimization for Snapshot Compressive Imaging


【深度学习】SENet:Squeeze-and-Excitation Networks


【深度学习】A New TwIST: Two-Step Iterative Shrinkage Thresholding Algorithms for Image Restoration


【深度学习】GFNet:Global Filter Networks for Image Classification


【深度学习】YOLO Series Survey


【深度学习】YOLO9000(YOLO V2): Better, Faster, Stronger


【深度学习】You Only Look Once(YOLO V1): Unified, Real-Time Object Detection


【深度学习】DeepLabV3+:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation


【深度学习】HarDNet: A Low Memory Traffic Network


【深度学习】PP-LiteSeg:A Superior Real-Time Semantic Segmentation Model


【深度学习】Segmentation Transformer(OCRNet): Object-Contextual Representations for Semantic Segmentation


【深度学习】SPP-net:Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition


【机器学习】Convexity II: Optimization Basics


【深度学习】PP-YOLOv2: A Practical Object Detector


【深度学习】YOLOX: Exceeding YOLO Series in 2021


【深度学习】PP-YOLOE: An evolved version of YOLO


【深度学习】PP-YOLO: An Effective and Efficient Implementation of Object Detector


【深度学习】ASGLD :Self-supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics


【深度学习】DIP:Deep Image Prior


【机器学习】Convexity I: Sets and Functions


【机器学习】Proximal Gradient Descent


【机器学习】Subgradient Method


【深度学习】AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network


【深度学习】CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image


【深度学习】Hyplex:Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders


【深度学习】Noise Distribution Adaptive Self-Supervised Image Denoising using Tweedie Distribution and Score Matching


【深度学习】USR-DU:Learning Degradation Uncertainty for Unsupervised Real-world Image Super-resolution


【机器学习】ADMM 推导与总结


【深度学习】LSM:Uncertainty Learning in Kernel Estimation for Multi-Stage Blind Image Super-Resolution


【深度学习】PnP-HSI:Deep plug-and-play priors for spectral snapshot compressive imaging


【深度学习】IDR: Self-Supervised Image Denoising via Iterative Data Refinement


【深度学习】DeepRFT:Deep Residual Fourier Transformation for Single Image Deblurring


【深度学习】CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution


【深度学习】Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks


【深度学习】UHDM:Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing


【深度学习】GST:Modeling Mask Uncertainty in Hyperspectral Image Reconstruction


【深度学习】Parameters 和 FLOPs 的计算


【深度学习】TLC:Improving Image Restoration by Revisiting Global Information Aggregation


【深度学习】Optimizers 推导和总结


【深度学习】ECCV 2022 low-level CV 论文汇总


【深度学习】RAM-DSIR:Generalizable Medical Image Segmentation via Random Amplitude Mixup and Domain-Specific Image Restoration


【深度学习】Deformable DETR:Deformable Transformers for End-to-End Object Detection


【深度学习】GAP-TV:GENERALIZED ALTERNATING PROJECTION BASED TOTAL VARIATION MINIMIZATION FOR COMPRESSIVE SENSING


【深度学习】HINet: Half Instance Normalization Network for Image Restoration


【深度学习】MIMO-UNet:Rethinking Coarse-to-Fine Approach in Single Image Deblurring


【深度学习】MIRNetv2:Learning Enriched Features for Fast Image Restoration and Enhancement


【深度学习】MPRNet:Multi-Stage Progressive Image Restoration


【深度学习】GAP-CCoT:Snapshot spectral compressive imaging reconstruction using convolution and contextual Transformer


【深度学习】Focal Frequency Loss for Image Reconstruction and Synthesis


【深度学习】FuncNet:Functional Neural Networks for Parametric Image Restoration Problems


【深度学习】Unfolding Taylor’s Approximations for Image Restoration


【深度学习】GAP-Net: GAP-net for Snapshot Compressive Imaging


【深度学习】ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing


【深度学习】Tensor FISTA-Net for Real-Time Snapshot Compressive Imaging


【深度学习】COAST:COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing


【深度学习】DGUNet:Deep Generalized Unfolding Networks for Image Restoration


【深度学习】BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging


【深度学习】Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning


【深度学习】Diffusion Models Made Easy


【深度学习】HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging


【深度学习】Quantization-aware Deep Optics for Diffractive Snapshot Hyperspectral Imaging


【深度学习】NAFNet:Simple Baselines for Image Restoration


【深度学习】Twins: Revisiting the Design of Spatial Attention in Vision Transformers


【深度学习】Restormer:Efficient Transformer for High-Resolution Image Restoration


【深度学习】MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications


【Research & Writing】draw.io Tutorial - Exerciese 1:添加 draw.io diagram 到 Confluence page


【深度学习】BIRNAT:Recurrent Neural Networks for Snapshot Compressive Imaging


【深度学习】KAIST:High-quality hyperspectral reconstruction using a spectral prior


【深度学习】MixFormer:Mixing Features across Windows and Dimensions


【深度学习】SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models


【深度学习】Deep Tensor ADMM-Net:Deep Tensor ADMM-Net for Snapshot Compressive Imaging


【深度学习】HDNet:High-resolution Dual-domain Learning for Spectral Compressive Imaging


【深度学习】λ-net:Reconstruct Hyperspectral Images from a Snapshot Measurement


【深度学习】CST:Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction


【深度学习】PnP-DIP-HSI:Self-supervised Neural Networks for Spectral Snapshot Compressive Imaging


【深度学习】TSA-Net:End-to-End Low Cost Compressive Spectral Imaging with Spatial-Spectral Self-Attention


【深度学习】DAUHST: Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging


【深度学习】MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction


【深度学习】Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction


【深度学习】Adaptive Nonlocal Sparse Representation for Dual-Camera Compressive Hyperspectral Imaging


【深度学习】High-Speed Hyperspectral Video Acquisition By Combining Nyquist and Compressive Sampling


【深度学习】Hyperspectral Image Reconstruction Using a Deep Spatial-Spectral Prior


【深度学习】HyperReconNet: Joint Coded Aperture Optimization and Image Reconstruction for Compressive Hyperspectral Imaging


【深度学习】Language Models Can See: Plugging Visual Controls in Text Generation


【深度学习】MST:Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction


【深度学习】DNU: Deep Non-local Unrolling for Computational Spectral Imaging


【深度学习】CLIP:Learning Transferable Visual Models From Natural Language Supervision


【深度学习】Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks


【深度学习】DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection


【深度学习】Spektral Creating a dataset


【深度学习】Spektral Data modes


【深度学习】Spektral


【机器学习】Understanding AUC - ROC Curve


【深度学习】A Gentle Introduction to Graph Neural Networks


【深度学习】SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS


【深度学习】Training Graph Convolutional Networks on Node Classification Task


【深度学习】Understanding Graph Convolutional Networks for Node Classification


【深度学习】HYPERSPECTRAL MEASUREMENTS FOR SHIP DETECTION USING AIRBORNE IMAGE DATA


【深度学习】Airborne ObjectDetection Using Hyperspectral Imaging: Deep Learning Review


【深度学习】Meta-Learning based Hyperspectral Target Detection using Siamese Network


【深度学习】Object Detection in Hyperspectral Images


【深度学习】Summary of Target Detection Algorithms


【深度学习】MCAN:Deep Modular Co-Attention Networks for Visual Question Answering


【深度学习】OPT: Open Pre-trained Transformer Language Models


【深度学习】LoFTR: Detector-Free Local Feature Matching with Transformers


【深度学习】Pythia v0.1: the Winning Entry to the VQA Challenge 2018


【深度学习】ClipCap: CLIP Prefix for Image Captioning


【深度学习】ECCV2022 workshop 竞赛汇总


【深度学习】Semisupervised Spectral Learning With Generative Adversarial Network for Hyperspectral Anomaly Detection


【深度学习】Neural Discrete Representation Learning


【深度学习】Training larger-than-memory PyTorch models using gradient checkpointing


【深度学习】UniT: Multimodal Multitask Learning with a Unified Transformer


【深度学习】ViLT:Vision-and-Language Transformer Without Convolution or Region Supervision


【深度学习】Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation


【深度学习】Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training


【深度学习】ERNIE-VILG: UNIFIED GENERATIVE PRE-TRAINING FOR BIDIRECTIONAL VISION-LANGUAGE GENERATION


【深度学习】Be Specific, Be Clear: Bridging Machine and Human Captions by Scene-Guided Transformer


【深度学习】A Picture is Worth a Thousand Words: A Unified System for Diverse Captions and Rich Images Generation


【深度学习】Kernelized Bayesian Softmax for Text Generation


【深度学习】Video-aided Unsupervised Grammar Induction


【深度学习】VLMO:Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts


【深度学习】Unified Contrastive Learning in Image-Text-Label Spac


【深度学习】Visually Grounded Compound PCFGs


【深度学习】VLGrammar: Grounded Grammar Induction of Vision and Language


【深度学习】UNSUPERVISED VISION-LANGUAGE GRAMMAR INDUCTION WITH SHARED STRUCTURE MODELING


【深度学习】VOLO: Vision Outlooker for Visual Recognition


【深度学习】X-VLM:Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts


【深度学习】LEMON:Scaling Up Vision-Language Pre-training for Image Captioning


【深度学习】TreeLSTM:Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks


【深度学习】A Novel Plug-in Module for Fine-Grained Visual Classification


【深度学习】ML-Decoder: Scalable and Versatile Classification Head


【深度学习】ORDERED NEURONS: INTEGRATING TREE STRUCTURES INTO RECURRENT NEURAL NETWORKS


【深度学习】Tree Transformer: Integrating Tree Structures into Self-Attention


【深度学习】On the Unreasonable Effectiveness of Centroids in Image Retrieval


【深度学习】VSE++: Improving Visual-Semantic Embeddings with Hard Negatives


【深度学习】Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations


【深度学习】ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora


【深度学习】Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers


【深度学习】ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation


【深度学习】ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding


【深度学习】ERNIE: Enhanced Representation through Knowledge Integration


【深度学习】ArcFace: Additive Angular Margin Loss for Deep Face Recognition


【深度学习】Image Generation from Scene Graphs


【深度学习】Are Vision-Language Transformers Learning Multimodal Representations?A Probing Perspective


【FastAI】07_sizing_and_tta


【深度学习】SGEITL:Scene Graph Enhanced Image-Text Learning for Visual Commonsense Reasoning


【深度学习】Hierarchical Cross-Modality Semantic Correlation Learning Model for Multimodal Summarization


【深度学习】LXMERT: Learning Cross-Modality Encoder Representations from Transformers


【深度学习】X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers


【深度学习】VISUALBERT: A SIMPLE AND PERFORMANT BASELINE FOR VISION AND LANGUAGE


【深度学习】UNIFYING ARCHITECTURES,TASKS, AND MODALITIES THROUGH A SIMPLE SEQUENCE-TO-SEQUENCELEARNING FRAMEWORK


【深度学习】A Comprehensive Survey of Scene Graphs: Generation and Application


【FastAI】06_multicat


【深度学习】Towards VQA Models That Can Read


【深度学习】SR3:Image Super-Resolution via Iterative Refinement


【深度学习】Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction


【深度学习】MOVIE:REVISITING MODULATED CONVOLUTIONS FOR VISUAL COUNTING AND BEYOND


【深度学习】In Defense of Grid Features for Visual Question Answering


【深度学习】Florence: A New Foundation Model for Computer Vision


【深度学习】How Much Can CLIP Benefit Vision-and-Language Tasks?


【深度学习】Align before Fuse: Vision and Language Representation Learning with Momentum Distillation


【深度学习】SIMVLM: SIMPLE VISUAL LANGUAGE MODEL PRE-TRAINING WITH WEAK SUPERVISION


【矩阵论】第三章: 线性空间与线性变换


【深度学习】Unbiased Scene Graph Generation from Biased Training


【深度学习】Graphical Contrastive Losses for Scene Graph Parsing


【深度学习】Graph R-CNN for Scene Graph Generation


【深度学习】Scene Graph Generation by Iterative Message Passing


【深度学习】Scene Graph Generation from Objects, Phrases and Region Captions


【深度学习】UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning


【深度学习】ERNIE-ViL:Knowledge Enhanced Vision-Language Representations through Scene Graphs


【深度学习】BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation


【深度学习】VinVL:Revisiting Visual Representations in Vision-Language Models


【深度学习】Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling


【深度学习】GATED GRAPH SEQUENCE NEURAL NETWORKS


【深度学习】Learning to Compose Dynamic Tree Structures for Visual Contexts


【深度学习】Unifying Multimodal Transformer for Bi-directional Image and Text Generation


【FastAI】05_pet_breeds


【机器学习】岭回归: Ridge Regression


【深度学习】VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions


【深度学习】Captioning Images Taken by People Who Are Blind


【Research & Competition】2022 CVPR workshop 竞赛汇总


【深度学习】A ConvNet for the 2020s


【深度学习】XLNet:Generalized Autoregressive Pretraining for Language Understanding


【深度学习】RoBERTa: A Robustly Optimized BERT Pretraining Approach


【FastAI】04_mnist_basics


【深度学习】YOLOP: You Only Look Once for Panoptic Driving Perception


【深度学习】GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models


【深度学习】On the Role of Scene Graphs in Image Captioning


【算法】图解leetcode


【深度学习】In Defense of Scene Graphs for Image Captioning


【FastAI】01_intro


【深度学习】Auto-Parsing Network for Image Captioning and Visual Question Answering


【深度学习】Unified Visual-Semantic Embeddings:Bridging Vision and Language with Structured Meaning Representations


【深度学习】如何理解 Pytorch 中的 gather 函数?


【深度学习】Auto-Encoding Scene Graphs for Image Captioning


【深度学习】Neural Motifs:Scene Graph Parsing with Global Context


2021

【矩阵论】第六章:广义逆


【算法】算法基础


【深度学习】Deep Learning Enabled Semantic Communication Systems


【矩阵论】历年考试


【矩阵论】第一章


【FastAI】FastAI


【深度学习】Scene graph For Image Captioning


【Geek】Mac OS 环境配置


【深度学习】fastai: A Layered API for Deep Learning


【Geek】搜索技术


【矩阵论】矩阵论复习


【深度学习】Grad-Cam相关


【深度学习】Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates


【Geek】To be a Vimer


【Geek】Some Funny Tricks & Experiments


【深度学习】Weights & Biases


【深度学习】Masked Autoencoders Are Scalable Vision Learners


【深度学习】Swin Transformer: Hierarchical Vision Transformer using Shifted Windows


【深度学习】Uformer:A General U-Shaped Transformer for Image Restoration


【深度学习】Revisiting ResNets: Improved Training and Scaling Strategies


【深度学习】ICCV2021 Image Captioning 相关论文


【深度学习】Oscar:Object-Semantics Aligned Pre-training for Vision-Language Tasks


【深度学习】MMCV 代码解读


【深度学习】MMLab Tools


【深度学习】CVPR2021:MultiModal 相关论文


【深度学习】ACM MM2021:Image Caption相关论文


【深度学习】Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering


【深度学习】VL-BERT:PRE-TRAINING OF GENERIC VISUAL-LINGUISTIC REPRESENTATIONS


【深度学习】Spatial As Deep: Spatial CNN for Traffic Scene Understanding


【机器学习】XGBoost: A Scalable Tree Boosting System


【深度学习】EfficientNetV2:Smaller Models and Faster Training


【深度学习】Enhance Multimodal Transformer With External Label And In-Domain Pretrain: Hateful Meme Challenge Winning Solution


【Kaggle】PetFinder


【Geek之路】Python数据可视化


【深度学习】Single-Cell Analysis


【d2l】Single Shot Multibox Detection


【d2l】 Multiscale Object Detection


【d2l】Parameter Servers


【机器学习】Log Derivative Trick


【d2l】Hardware


【深度学习】SCST:Self-critical Sequence Training for Image Captioning


【d2l】Automatic Parallelism


【d2l】Asynchronous Computation


【d2l】Compilers and Interpreters


【d2l】 Learning Rate Scheduling


【深度学习】CycleGAN:Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks


【d2l】Adam


【d2l】Adadelta


【d2l】RMSProp


【d2l】Adagrad


【d2l】Momentum


【d2l】Stochastic Gradient Descent


【d2l】Gradient Descent


【深度学习】Meshed-Memory Transformer for Image Captioning


【深度学习】ViT:An Image is Worth 16 X 16 Words: Transformers for Image Recognition at Sscale


【深度学习】VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning


【d2l】Sequence to Sequence Learning


【Geek】Pythonic


【d2l】Convexity


【d2l】Optimization and Deep Learning


【d2l】束搜索:Beam Search


【深度学习】Video-to-Video Synthesis


【深度学习】SPICE: Semantic Propositional Image Caption Evaluation


【深度学习】GPT:Improving Language Understanding by Generative Pre-Training


【机器学习】模式识别


【深度学习】图像字幕生成


【d2l】Numerical Stability and Initialization


【d2l】环境和分布偏移


【深度学习】XMC-GAN: Cross-Modal Contrastive Learning for Text-to-Image Generation


【d2l】Model Selection, Underfitting, and Overfitting


【d2l】Multilayer Perceptrons


【d2l】Linear Regression


【深度学习】GPT-2:Language Models are Unsupervised Multitask Learners


【深度学习】MindSpore手册


【机器学习】sklearn手册及机器学习方法


【深度学习】目标检测比赛技巧总结


【深度学习】ResNet几种变体


【d2l】Region-based CNNs (R-CNNs)


【深度学习】Improving Language Understanding by Generative Pre-Training


【深度学习】Attention总结


【d2l】Transformer


【d2l】Self-Attention and Positional Encoding


【深度学习】PaddlePaddle手册


【Research & Writing】Office Learning


【d2l】Multi-Head Attention


【d2l】Bahdanau Attention


【d2l】Attention Scoring Functions


【深度学习】CLIP: Connecting Text and Images


【深度学习】DALL·E: Creating Images from Text


【d2l】Attention Pooling: Nadaraya-Watson Kernel Regression


【d2l】Attention Cues


【机器学习】支持向量机SVM


【深度学习】OpenMMLab


【d2l】Bidirectional Encoder Representations from Transformers (BERT)


【深度学习】Huggingface 手册


【d2l】Finding Synonyms and Analogies


【机器学习】SVM、AlexNet、VGG收敛速度对比


【d2l】Subword Embedding


【d2l】Word Embedding with Global Vectors (GloVe)


【深度学习】PyTorch Lightning 及 TorchMetric 手册


【d2l】 Pretraining word2vec


【深度学习】InfoGAN论文阅读


【深度学习】Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation


【深度学习】Semantic Image Manipulation Using Scene Graphs


【深度学习】Semantically Multi-modal Image Synthesis


【深度学习】SketchyCOCO: Image Generation from Freehand Scene Sketches


【深度学习】Specifying Object Attributes and Relations in Interactive Scene Generation


【深度学习】StyleGAN v2论文阅读


【深度学习】SEAN论文阅读


【Research & Writing】中英文写作语料库


【d2l】The Dataset for Pretraining Word Embedding


【深度学习 In-Domain GAN Inversion for Real Image Editing


【深度学习】Navigating the GAN Parameter Space for Semantic Image Editing


【深度学习】数据集及评价指标


【d2l】Approximate Training


【d2l】d2l api手册


【d2l】Word Embedding (word2vec)


【Research & Writing】英语语法


【深度学习】Image Synthesis with Adversarial Networks: a Comprehensive Survey and Case Studies


【Geek】RSS 相关


【深度学习】Knowledge-guided semantic computing network


【d2l】Anchor Boxes


【d2l】Object Detection and Bounding Boxes


【深度学习】Faster R-CNN论文阅读


【Geek之路】Wenny开发日记


【深度学习】Neural Kinematic Networks for Unsupervised Motion Retargetting


【深度学习】Skeleton-Aware Networks for Deep Motion Retargeting


【深度学习】Pix2PixHD论文阅读


【深度学习】Pix2Pix:Image-to-Image Translation with Conditional Adversarial Networks


【深度学习】Everybody Dance Now


【深度学习】SSD: Single Shot MultiBox Detector


【深度学习】Understanding LSTM Networks


【深度学习】RNN的前向和反向传播推导


【Geek之路】走进聊天机器人


2020

【Research & Writing】雅思作文模板


【计算方法】线性方程组的数值解法


【计算智能】模糊运算


【计算智能】遗传算法


【深度学习】Res2Net论文阅读


【Research & Writing】会议&期刊&比赛


【深度学习】Attention is all you need


【Geek之路】效率提升软件


【深度学习】DenseNet论文阅读


【深度学习】ResNet论文阅读


【计算方法】数值积分与数值微分


【深度学习】GoogLeNet论文阅读


【深度学习】循环神经网络


【计算方法】最佳逼近和最小二乘法


【深度学习】VGGNet论文阅读


【计算方法】插值法 - 2


【机器学习】065--引⼊时间轴:动态图模型 的共性与特征


【深度学习】NLP相关工具及其使用


【机器学习】064--有向图模型与条件独⽴性


【计算方法】插值法 - 1


【机器学习】063--概率图模型导论


【计算方法】范数与内积


【机器学习】062--⻢尔科夫链蒙特卡洛⽅ 法:从 M-H 到 Gibbs


【机器学习】061--采样绝佳途径:⻢尔科夫 链及其稳态


【机器学习】060--随机近似⽅法初步


【机器学习】059--统计推断的基本思想和分类


【机器学习】058--连续域上的无限维:高斯过程介绍


【机器学习】057--⾼斯混合模型的参数求解


【机器学习】056--探索高斯混合模型:EM 迭代实践


【机器学习】055--探索 EM 公式的底层逻辑与由来


【机器学习】053--含有隐变量的参数估计问 题


【深度学习】Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models


【机器学习】052--朴素贝叶斯:基于条件独立性假设


【机器学习】051--高斯判别分析:基于高斯分布的假设前提


【机器学习】050--判别 or ⽣成:从逻辑回 归说起


【机器学习】049--⾼斯噪声:最小⼆乘线性 估计的新视⻆


【机器学习】048--多元⾼斯分布:参数特征和⼏何意义


【机器学习】047--⼀维⾼斯分布:极⼤似然 与⽆偏性


【机器学习】046--多元函数的极值(下):⽜ 顿法与向量微分


【深度学习】Learning to Compose Dynamic Tree Structures for Visual Contexts


【机器学习】045--多元函数的极值(中):最速下降法


【机器学习】044--多元函数的极值(上):梯 度法基础


【机器学习】043--⼀元函数的极值:运⽤迭代法


【机器学习】Hazard of Overfitting


【机器学习】Linear Models for Classification


【机器学习】Logistic Regression


【机器学习】Nonlinear Transformation


【机器学习】Linear Regression


【机器学习】Noise and Error


【机器学习】The VC Dimension


【机器学习】Theory of Generalization


【机器学习】Feasibility of Learning


【机器学习】Training versus Testing


【机器学习】Types of Learning


【机器学习】Learning to Answer Yes-No


【机器学习】042--导引:最优化的基本问题 和存在条件


【机器学习】041--多元函数的梯度及其应⽤


【机器学习】040--多元函数的微分及泰勒近似


【机器学习】039--多元函数及其偏导数


【机器学习】038--函数近似与泰勒级数


【机器学习】036--主成分分析(下):奇异值 分解与数据降维


【机器学习】035--主成分分析(中):奇异值 分解的原理与通⽤性


【mark】技术栈、科研方向、论文目录、书籍目录等


【机器学习】032--变化中的不变:特征值与 特征向量


【机器学习】031--简而美的相似对⻆矩阵


【机器学习】030--相似矩阵与相似变换


【机器学习】028--寻找最近:空间中的向量投影


【机器学习】025--矩阵与映射中的“逆”


【机器学习】024--矩阵的核⼼(下):空间映 射


【机器学习】023--矩阵的核⼼(上):向量变 换


【机器学习】022--空间:从向量和基底谈起


【机器学习】021--状态解码:隐马尔科夫模型隐含状态揭秘


【机器学习】020--概率估计:隐⻢尔科夫模 型观测序列描述


【机器学习】019--隐⻢尔科夫模型:明暗两条线


【机器学习】018--⻢尔科夫链蒙特卡洛⽅ 法:通⽤采样引擎


【机器学习】016--基于⻢尔科夫链的近似采样


【机器学习】015--变与不变:⻢尔科夫链的 极限与稳态


【机器学习】014--状态转移:初识马尔科夫链


【机器学习】009--极限思维:大数定理与中心极限定理


【深度学习】MTCNN论文阅读及其实现


【机器学习】004--离散型随机变量:分布与数字特征


【机器学习】003--事件的关系:深入理解独立性


【机器学习】002--理论基石:条件概率、独立性与贝叶斯


【强化学习】Model-free Prediction and Control


【强化学习】强化学习环境相关


【强化学习】强化学习相关概念


【强化学习】马尔科夫决策过程(MDP)


【Geek之路】Linux相关命令


【强化学习】李宏毅强化学习课程笔记


【Mark】每日必看网站


【学会理财】基金知识


【转载】深度解密换脸应用Deepfake


【深度学习笔录】SNGAN论文阅读及其实现


【深度学习笔录】SAGAN论文阅读及其实现


【深度学习笔录】SPADE(GauGAN)论文阅读及其实现


【深度学习笔录】StyleGAN论文阅读及其实现


【深度学习笔录】ProGAN论文阅读及其实现


【深度学习笔录】AdaIN论文阅读及其实现


【离散数学】代数系统和图论


【机器学习】损失函数以及评价指标


【深度学习笔录】WGAN-GP论文阅读及其实现


【学会理财】虚拟货币相关概念


【深度学习笔录】mxnet学习笔记


【计算机网络】计算机网络


【xdu_ccf】西安电子科技大学机试以及部分CCF题解


【操作系统】操作系统


【Geek之路】Chrome使用技巧


【计算机网络】数据链路层


【机器学习笔录】深度学习图像处理相关库


【计算机网络】物理层.md


【离散数学】集合和二元关系


【Geek之路】《剑指offer》思路及代码合集


【操作系统】进程管理


【离散数学】谓词逻辑


【Geek之路】C、C++语法及Trick


【计算机网络】绪论


【操作系统】中断


【操作系统】绪论


【离散数学】命题逻辑


【深度学习笔录】FaceShifter论文阅读及其实现


【Geek之路】Windows美化及使用技巧


【Geek之路】markdown及LaTeX常用语法


【深度学习笔录】VAEs推导


【Geek之路】翻墙工具及机场备份


【深度学习笔录】VAE-GAN论文阅读及其实现


【深度学习笔录】CGAN论文阅读及其实现


【深度学习笔录】CVAE论文阅读及其实现


【深度学习笔录】VAE论文阅读及其实现


【机器学习笔录】交叉熵、KL散度、JS散度以及Wasserstein距离


【Geek之路】Python画图相关库及工具使用


【Geek之路】Python语法与Python Tricks


【机器学习】python 工具库


【机器学习】机器学习相关库及工具使用


【Geek之路】Colab使用手册


【Geek之路】Git使用手册


【深度学习笔录】GANs推导


【深度学习笔录】WGAN论文阅读及其PyTorch实现


【深度学习笔录】DCGAN论文阅读及其Pytorch实现


2019

【深度学习笔录】GAN论文阅读及Pytorch实现


【Geek之路】开发环境搭建及工具


【深度学习笔录】Deepfacelab中的概念及参数


【深度学习笔录】Windows下Docker深度学习环境配置


【Geek之路】使用github搭建博客


【Geek之路】Docker手册


【算法与数据结构】树


【数据结构】排序


【算法与数据结构】图


【数据结构】查找


【机器学习】PyTorch学习笔记


【机器视觉笔录】OpenCV小案例实战


2018

【机器学习笔录】再论线性回归和逻辑回归


【机器视觉笔录】OpenCV特征提取与检测


【嵌入式&物联网】记一次汇编题目


【机器学习笔录】OpenCV中的API及用法


【Hacker之梦】Scrapy框架爬取URP教务系统


【心声】2018年ICAN国际创新创业大赛体会心得


【心声】写一份计划


【Hacker之梦】MongoDB数据库的基本概念及操作


【机器学习笔录】机器学习中一些函数的概念及应用[二]


【机器学习笔录】机器学习中一些函数的概念及应用[一]


【深度学习笔录】Tensorflow及Keras学习笔记


【爬坑树莓派】从零配置环境


【机器学习笔录】线性回归与逻辑回归


【过好生活】好物清单


【Geek】Awesome Things