https://github.com/xinntao/EDVR
공식 코드EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 17
- 평가표
- 31
- 보존된 평가 기록
- 235
Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
<span style="color:grey; opacity: 0.6">( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xinntao/ESRGAN
공식 코드ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/xinntao/Real-ESRGAN
공식 코드Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
https://github.com/xiongjunguan/draco
공식 코드https://github.com/xiu-cs/iganet
공식 코드Interweaved Graph and Attention Network for 3D Human Pose Estimation
https://github.com/xmindflow/hca-net
공식 코드HCA-Net: Hierarchical Context Attention Network for Intervertebral Disc Semantic Labeling
https://github.com/xpixelgroup/rethinkvsralignment
공식 코드https://github.com/xtudbxk/tmp
공식 코드TMP: Temporal Motion Propagation for Online Video Super-Resolution
https://github.com/xuelunshen/gim
공식 코드GIM: Learning Generalizable Image Matcher From Internet Videos
https://github.com/xunshanman/mvgformer
공식 코드Multiple View Geometry Transformers for 3D Human Pose Estimation
https://github.com/xuxy09/RSC-Net
공식 코드3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning
https://github.com/xuxy09/smpler
공식 코드SMPLer: Taming Transformers for Monocular 3D Human Shape and Pose Estimation
https://github.com/xuzhang1199/clamp
공식 코드CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal Pose
https://github.com/xy-boy/blind-satellite-vsr
공식 코드https://github.com/xy-boy/lgtd
공식 코드Local-Global Temporal Difference Learning for Satellite Video Super-Resolution
https://github.com/xy-boy/tdmvsr
공식 코드Local-Global Temporal Difference Learning for Satellite Video Super-Resolution
https://github.com/xyonglu/cmsa
공식 코드https://github.com/xzhouzeng/prpose
공식 코드Probablistic Restoration with Adaptive Noise Sampling for 3D Human Pose Estimation
https://github.com/yanghai-1218/pseudoflow
공식 코드Pseudo Flow Consistency for Self-Supervised 6D Object Pose Estimation
https://github.com/yanghai-1218/radet
공식 코드https://github.com/yanghai-1218/scflow
공식 코드Shape-Constraint Recurrent Flow for 6D Object Pose Estimation
https://github.com/yanghb22-fdu/hi3d-official
공식 코드Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Models
https://github.com/yangsenius/PoseNFS
공식 코드https://github.com/yangsenius/TransPose
공식 코드https://github.com/yangsenius/int_hmr_model
공식 코드Capturing the motion of every joint: 3D human pose and shape estimation with independent tokens
https://github.com/yangsenius/ssa
공식 코드https://github.com/yangzhou12/ncrl
공식 코드None Class Ranking Loss for Document-Level Relation Extraction
https://github.com/yanjh97/transgrasp
공식 코드https://github.com/yanmin-wu/EAO-SLAM
공식 코드EAO-SLAM: Monocular Semi-Dense Object SLAM Based on Ensemble Data Association
https://github.com/yaochih/gcvd-release
공식 코드Globally Consistent Video Depth and Pose Estimation with Efficient Test-Time Training
https://github.com/yaqding/pose_monodepth
공식 코드RePoseD: Efficient Relative Pose Estimation With Known Depth Information
https://github.com/ybhbingo/mmfi_dataset
공식 코드MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing
https://github.com/ybkscht/EfficientPose
공식 코드https://github.com/ybkurt/vift
공식 코드Causal Transformer for Fusion and Pose Estimation in Deep Visual Inertial Odometry
https://github.com/yc-che/op-align
공식 코드https://github.com/yc4ny/SVAD
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.