3. 

        2. CVPR 2021 論文和開源項(xiàng)目合集(Papers with Code)
        共
                13809字，需瀏覽
                    28分鐘
                
         ·
        2021-03-13 15:30
        
                    

                    
                    
                    
                    


        【CVPR 2021 論文開源目錄】
        https://github.com/amusi/CVPR2021-Papers-with-Code

        • Backbone
        • NAS
        • GAN
        • Visual Transformer
        • 自監(jiān)督(Self-Supervised)
        • 目標(biāo)檢測(cè)(Object Detection)
        • 實(shí)例分割(Instance Segmentation)
        • 全景分割(Panoptic Segmentation)
        • 視頻理解/行為識(shí)別(Video Understanding)
        • 人臉識(shí)別(Face Recognition)
        • 人臉活體檢測(cè)(Face Anti-Spoofing)
        • Deepfake檢測(cè)(Deepfake Detection)
        • 人臉年齡估計(jì)(Age-Estimation)
        • 人臉解析(Human Parsing)
        • 超分辨率(Super-Resolution)
        • 圖像恢復(fù)(Image Restoration)
        • 3D目標(biāo)檢測(cè)(3D Object Detection)
        • 3D語(yǔ)義分割(3D Semantic Segmentation)
        • 3D目標(biāo)跟蹤(3D Object Tracking)
        • 3D點(diǎn)云配準(zhǔn)(3D Point Cloud Registration)
        • 6D位姿估計(jì)(6D Pose Estimation)
        • 深度估計(jì)(Depth Estimation)
        • 對(duì)抗樣本(Adversarial-Examples)
        • 圖像檢索(Image Retrieval)
        • Zero-Shot Learning
        • 視覺推理(Visual Reasoning)
        • "人-物"交互(HOI)檢測(cè)
        • 陰影去除(Shadow Removal)
        • 數(shù)據(jù)集(Datasets)
        • 其他(Others)
        • 不確定中沒中(Not Sure)


        Backbone
        Coordinate Attention for Efficient Mobile Network Design
        • Paper: https://arxiv.org/abs/2103.02907
        • Code: https://github.com/Andrew-Qibin/CoordAttention
        Inception Convolution with Efficient Dilation Search
        • Paper: https://arxiv.org/abs/2012.13587
        • Code: None
        RepVGG: Making VGG-style ConvNets Great Again
        • Paper: https://arxiv.org/abs/2101.03697
        • Code: https://github.com/DingXiaoH/RepVGG

        NAS
        Inception Convolution with Efficient Dilation Search
        • Paper: https://arxiv.org/abs/2012.13587
        • Code: None

        GAN
        Training Generative Adversarial Networks in One Stage
        • Paper: https://arxiv.org/abs/2103.00430
        • Code: None
        Closed-Form Factorization of Latent Semantics in GANs
        • Homepage: https://genforce.github.io/sefa/
        • Paper: https://arxiv.org/abs/2007.06600
        • Code: https://github.com/genforce/sefa
        Anycost GANs for Interactive Image Synthesis and Editing
        • Paper: https://arxiv.org/abs/2103.03243
        • Code: https://github.com/mit-han-lab/anycost-gan
        Image-to-image Translation via Hierarchical Style Disentanglement
        • Paper: https://arxiv.org/abs/2103.01456
        • Code: https://github.com/imlixinyang/HiSD

        Visual Transformer
        End-to-End Video Instance Segmentation with Transformers
        • Paper(Oral): https://arxiv.org/abs/2011.14503
        • Code: None
        UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
        • Paper(Oral): https://arxiv.org/abs/2011.09094
        • Code: https://github.com/dddzg/up-detr
        End-to-End Human Object Interaction Detection with HOI Transformer
        • Paper: https://arxiv.org/abs/2103.04503
        • Code: https://github.com/bbepoch/HoiTransformer
        Transformer Interpretability Beyond Attention Visualization
        • Paper: https://arxiv.org/abs/2012.09838
        • Code: https://github.com/hila-chefer/Transformer-Explainability

        自監(jiān)督
        Dense Contrastive Learning for Self-Supervised Visual Pre-Training
        • Paper: https://arxiv.org/abs/2011.09157
        • Code: https://github.com/WXinlong/DenseCL

        目標(biāo)檢測(cè)(Object Detection)
        UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
        • Paper(Oral): https://arxiv.org/abs/2011.09094
        • Code: https://github.com/dddzg/up-detr
        General Instance Distillation for Object Detection
        • Paper: https://arxiv.org/abs/2103.02340
        • Code: None
        Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
        • Paper: https://arxiv.org/abs/2103.01903
        • Code: None
        There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
        • Homepage: http://rl.uni-freiburg.de/research/multimodal-distill
        • Paper: https://arxiv.org/abs/2103.01353
        • Code: http://rl.uni-freiburg.de/research/multimodal-distill
        Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
        • Paper: https://arxiv.org/abs/2011.12885
        • Code: https://github.com/implus/GFocalV2
        Multiple Instance Active Learning for Object Detection
        • Paper: https://github.com/yuantn/MIAL/raw/master/paper.pdf
        • Code: https://github.com/yuantn/MIAL
        Towards Open World Object Detection
        • Paper: https://arxiv.org/abs/2103.02603
        • Code: https://github.com/JosephKJ/OWOD

        實(shí)例分割(Instance Segmentation)
        End-to-End Video Instance Segmentation with Transformers
        • Paper(Oral): https://arxiv.org/abs/2011.14503
        • Code: None
        Zero-shot instance segmentation（Not Sure）
        • Paper: None
        • Code: https://github.com/CVPR2021-pape-id-1395/CVPR2021-paper-id-1395

        全景分割(Panoptic Segmentation)
        Cross-View Regularization for Domain Adaptive Panoptic Segmentation
        • Paper: https://arxiv.org/abs/2103.02584
        • Code: None

        視頻理解/行為識(shí)別(Video Understanding)
        TDN: Temporal Difference Networks for Efficient Action Recognition
        • Paper: https://arxiv.org/abs/2012.10071
        • Code: https://github.com/MCG-NJU/TDN

        人臉識(shí)別(Face Recognition)
        WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
        • Homepage: https://www.face-benchmark.org/
        • Paper: https://arxiv.org/abs/2103.04098
        • Dataset: https://www.face-benchmark.org/
        When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
        • Paper(Oral): https://arxiv.org/abs/2103.01520
        • Code: https://github.com/Hzzone/MTLFace
        • Dataset: https://github.com/Hzzone/MTLFace

        人臉活體檢測(cè)(Face Anti-Spoofing)
        Cross Modal Focal Loss for RGBD Face Anti-Spoofing
        • Paper: https://arxiv.org/abs/2103.00948
        • Code: None

        Deepfake檢測(cè)(Deepfake Detection)
        Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
        • Paper：https://arxiv.org/abs/2103.01856
        • Code: None
        Multi-attentional Deepfake Detection
        • Paper：https://arxiv.org/abs/2103.02406
        • Code: None

        人臉年齡估計(jì)(Age Estimation)
        PML: Progressive Margin Loss for Long-tailed Age Classification
        • Paper: https://arxiv.org/abs/2103.02140
        • Code: None

        人體解析(Human Parsing)
        Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing
        • Paper: https://arxiv.org/abs/2103.04570
        • Code: https://github.com/tfzhou/MG-HumanParsing

        超分辨率(Super-Resolution)
        ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
        • Paper: https://arxiv.org/abs/2103.04039
        • Code: https://github.com/Xiangtaokong/ClassSR
        AdderSR: Towards Energy Efficient Image Super-Resolution
        • Paper: https://arxiv.org/abs/2009.08891
        • Code: None

        圖像恢復(fù)(Image Restoration)
        Multi-Stage Progressive Image Restoration
        • Paper: https://arxiv.org/abs/2102.02808
        • Code: https://github.com/swz30/MPRNet

        3D目標(biāo)檢測(cè)(3D Object Detection)
        SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
        • Paper: None
        • Code: https://github.com/Vegeta2020/SE-SSD
        Center-based 3D Object Detection and Tracking
        • Paper: https://arxiv.org/abs/2006.11275
        • Code: https://github.com/tianweiy/CenterPoint
        Categorical Depth Distribution Network for Monocular 3D Object Detection
        • Paper: https://arxiv.org/abs/2103.01100
        • Code: None

        3D語(yǔ)義分割(3D Semantic Segmentation)
        Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
        • Homepage: https://github.com/QingyongHu/SensatUrban
        • Paper: http://arxiv.org/abs/2009.03137
        • Code: https://github.com/QingyongHu/SensatUrban
        • Dataset: https://github.com/QingyongHu/SensatUrban

        3D目標(biāo)跟蹤(3D Object Trancking)
        Center-based 3D Object Detection and Tracking
        • Paper: https://arxiv.org/abs/2006.11275
        • Code: https://github.com/tianweiy/CenterPoint

        3D點(diǎn)云配準(zhǔn)(3D Point Cloud Registration)
        PREDATOR: Registration of 3D Point Clouds with Low Overlap
        • Paper: https://arxiv.org/abs/2011.13005
        • Code: https://github.com/ShengyuH/OverlapPredator

        6D位姿估計(jì)(6D Pose Estimation)
        FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
        • Paper: https://arxiv.org/abs/2103.02242
        • Code: https://github.com/ethnhe/FFB6D

        深度估計(jì)
        Depth from Camera Motion and Object Detection
        • Paper: https://arxiv.org/abs/2103.01468
        • Code: https://github.com/griffbr/ODMD
        • Dataset: https://github.com/griffbr/ODMD

        對(duì)抗樣本
        Natural Adversarial Examples
        • Paper: https://arxiv.org/abs/1907.07174
        • Code: https://github.com/hendrycks/natural-adv-examples

        圖像檢索(Image Retrieval)
        QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
        • Paper: https://arxiv.org/abs/2103.02927
        • Code: None

        Zero-Shot Learning
        Counterfactual Zero-Shot and Open-Set Visual Recognition
        • Paper: https://arxiv.org/abs/2103.00887
        • Code: https://github.com/yue-zhongqi/gcm-cf

        視覺推理(Visual Reasoning)
        Transformation Driven Visual Reasoning
        • homepage: https://hongxin2019.github.io/TVR/
        • Paper: https://arxiv.org/abs/2011.13160
        • Code: https://github.com/hughplay/TVR

        "人-物"交互(HOI)檢測(cè)
        End-to-End Human Object Interaction Detection with HOI Transformer
        • Paper: https://arxiv.org/abs/2103.04503
        • Code: https://github.com/bbepoch/HoiTransformer

        陰影去除(Shadow Removal)
        Auto-Exposure Fusion for Single-Image Shadow Removal
        • Paper: https://arxiv.org/abs/2103.01255
        • Code: https://github.com/tsingqguo/exposure-fusion-shadow-removal

        數(shù)據(jù)集(Datasets)
        Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food
        • Paper: https://arxiv.org/abs/2103.03375
        • Dataset: None
        Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
        • Homepage: https://github.com/QingyongHu/SensatUrban
        • Paper: http://arxiv.org/abs/2009.03137
        • Code: https://github.com/QingyongHu/SensatUrban
        • Dataset: https://github.com/QingyongHu/SensatUrban
        When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
        • Paper(Oral): https://arxiv.org/abs/2103.01520
        • Code: https://github.com/Hzzone/MTLFace
        • Dataset: https://github.com/Hzzone/MTLFace
        Depth from Camera Motion and Object Detection
        • Paper: https://arxiv.org/abs/2103.01468
        • Code: https://github.com/griffbr/ODMD
        • Dataset: https://github.com/griffbr/ODMD
        There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
        • Homepage: http://rl.uni-freiburg.de/research/multimodal-distill
        • Paper: https://arxiv.org/abs/2103.01353
        • Code: http://rl.uni-freiburg.de/research/multimodal-distill
        Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
        • Paper: https://arxiv.org/abs/2012.02206
        • Code: https://github.com/daveredrum/Scan2Cap
        • Dataset: https://github.com/daveredrum/ScanRefer
        There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
        • Paper: https://arxiv.org/abs/2103.01353
        • Code: http://rl.uni-freiburg.de/research/multimodal-distill
        • Dataset: http://rl.uni-freiburg.de/research/multimodal-distill

        其他(Others)
        Knowledge Evolution in Neural Networks
        • Paper(Oral): https://arxiv.org/abs/2103.05152
        • Code: https://github.com/ahmdtaha/knowledge_evolution
        Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
        • Paper: https://arxiv.org/abs/2103.02148
        • Code: https://github.com/guopengf/FLMRCM
        SGP: Self-supervised Geometric Perception
        • Oral
        • Paper: https://arxiv.org/abs/2103.03114
        • Code: https://github.com/theNded/SGP
        Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
        • Paper: https://arxiv.org/abs/2103.02148
        • Code: https://github.com/guopengf/FLMRCM
        Diffusion Probabilistic Models for 3D Point Cloud Generation
        • Paper: https://arxiv.org/abs/2103.01458
        • Code: https://github.com/luost26/diffusion-point-cloud
        Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
        • Paper: https://arxiv.org/abs/2012.02206
        • Code: https://github.com/daveredrum/Scan2Cap
        • Dataset: https://github.com/daveredrum/ScanRefer
        There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
        • Paper: https://arxiv.org/abs/2103.01353
        • Code: http://rl.uni-freiburg.de/research/multimodal-distill
        • Dataset: http://rl.uni-freiburg.de/research/multimodal-distill

        不確定中沒中(Not Sure)
        CT Film Recovery via Disentangling Geometric Deformation and Photometric Degradation: Simulated Datasets and Deep Models
        • Paper: none
        • Code: https://github.com/transcendentsky/Film-Recovery
        Toward Explainable Reflection Removal with Distilling and Model Uncertainty
        • Paper: none
        • Code: https://github.com/ytpeng-aimlab/CVPR-2021-Toward-Explainable-Reflection-Removal-with-Distilling-and-Model-Uncertainty
        DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation
        • Paper: none
        • Code: https://github.com/lhaippp/DeepOIS
        Exploring Adversarial Fake Images on Face Manifold
        • Paper: none
        • Code: https://github.com/ldz666666/Style-atk
        Uncertainty-Aware Semi-Supervised Crowd Counting via Consistency-Regularized Surrogate Task
        • Paper: none
        • Code: https://github.com/yandamengdanai/Uncertainty-Aware-Semi-Supervised-Crowd-Counting-via-Consistency-Regularized-Surrogate-Task
        Temporal Contrastive Graph for Self-supervised Video Representation Learning
        • Paper: none
        • Code: https://github.com/YangLiu9208/TCG
        Boosting Monocular Depth Estimation Models to High-Resolution via Context-Aware Patching
        • Paper: none
        • Code: https://github.com/ouranonymouscvpr/cvpr2021_ouranonymouscvpr
        Fast and Memory-Efficient Compact Bilinear Pooling
        • Paper: none
        • Code: https://github.com/cvpr2021kp2/cvpr2021kp2
        Identification of Empty Shelves in Supermarkets using Domain-inspired Features with Structural Support Vector Machine
        • Paper: none
        • Code: https://github.com/gapDetection/cvpr2021
        Estimating A Child's Growth Potential From Cephalometric X-Ray Image via Morphology-Aware Interactive Keypoint Estimation
        • Paper: none
        • Code: https://github.com/interactivekeypoint2020/Morph
        https://github.com/ShaoQiangShen/CVPR2021
        https://github.com/gillesflash/CVPR2021
        https://github.com/anonymous-submission1991/BaLeNAS
        https://github.com/cvpr2021dcb/cvpr2021dcb
        https://github.com/anonymousauthorCV/CVPR2021_PaperID_8578
        https://github.com/AldrichZeng/FreqPrune
        https://github.com/Anonymous-AdvCAM/Anonymous-AdvCAM
        https://github.com/ddfss/datadrive-fss

        
                
        瀏覽
                    59
        點(diǎn)贊
    
        評(píng)論
    
        收藏
    
        分享
        
        手機(jī)掃一掃分享
        分享
    
        
        舉報(bào)
    
        評(píng)論
        圖片
        表情
        推薦
        
        點(diǎn)贊
    
        評(píng)論
    
        收藏
    
        分享
        
        手機(jī)掃一掃分享
        分享
    
        
        舉報(bào)
    
        

          

          3. 

              2. 
囯产精品久久久久久久久久免费
|
逼逼网址
|
在线观看成人网
|
欧美激情bb
|
草莓樱桃西瓜榴莲通用包装盒
|