https://github.com/ckkelvinchan/realbasicvsr
공식 코드Investigating Tradeoffs in Real-World Video Super-Resolution
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/claudiom4sir/stablevsr
공식 코드https://github.com/claudiunz/tnwahi-appakrcs
공식 코드https://github.com/cleardusk/3DDFA
공식 코드https://github.com/cliffordlab/edgecameratracking
공식 코드https://github.com/climbingdaily/SLOPER4D
공식 코드SLOPER4D: A Scene-Aware Dataset for Global 4D Human Pose Estimation in Urban Environments
https://github.com/climbingdaily/hsc4d
공식 코드https://github.com/clovaai/meev
공식 코드https://github.com/cmdi-dlut/SMPR
공식 코드https://github.com/cnjianliu/awesome-object-pose-estimation
공식 코드Deep Learning-Based Object Pose Estimation: A Comprehensive Survey
https://github.com/cnjianliu/diff9d
공식 코드Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation
https://github.com/cnjianliu/monodiff9d
공식 코드MonoDiff9D: Monocular Category-Level 9D Object Pose Estimation via Diffusion Model
https://github.com/cnjianliu/sinref-6d
공식 코드Novel Object 6D Pose Estimation with a Single Reference View
https://github.com/cnqiangfu/PL-VINS
공식 코드PL-VINS: Real-Time Monocular Visual-Inertial SLAM with Point and Line Features
https://github.com/codeslake/RefVSR
공식 코드Reference-based Video Super-Resolution Using Multi-Camera Video Triplets
https://github.com/cognitive-robots/sem-gat
공식 코드SEM-GAT: Explainable Semantic Pose Estimation using Learned Graph Attention
https://github.com/comedialkb/learning_with_passive_optical_nonlinear_mapping
공식 코드Nonlinear optical encoding enabled by recurrent linear scattering
https://github.com/complight/spectrack
공식 코드SpecTrack: Learned Multi-Rotation Tracking via Speckle Imaging
https://github.com/continental/6img-to-3d
공식 코드6Img-to-3D: Few-Image Large-Scale Outdoor Driving Scene Reconstruction
https://github.com/cool-xuan/x-hrnet
공식 코드X-HRNet: Towards Lightweight Human Pose Estimation with Spatially Unidimensional Self-Attention
https://github.com/coulsonlee/stdo-cvpr2023
공식 코드Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting
https://github.com/cpantazop/handrepo
공식 코드Monocular 3D Hand Pose Estimation with Implicit Camera Alignment
https://github.com/csbhr/Deep-Blind-VSR
공식 코드https://github.com/csbhr/self-blind-vsr
공식 코드https://github.com/cseeyangchen/dt-pose
공식 코드Towards Robust and Realistic Human Pose Estimation via WiFi Signals
https://github.com/csiro-robotics/spectralgv
공식 코드Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization
https://github.com/csxmli2016/DFDNet
공식 코드Blind Face Restoration via Deep Multi-scale Component Dictionaries
https://github.com/cszn/BSRGAN
공식 코드Designing a Practical Degradation Model for Deep Blind Image Super-Resolution
https://github.com/cszn/SRMD
공식 코드Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
https://github.com/ctu-mrs/rms
공식 코드RMS: Redundancy-Minimizing Point Cloud Sampling for Real-Time Pose Estimation
https://github.com/cuge1995/u6da
공식 코드Adversarial samples for deep monocular 6D object pose estimation
https://github.com/cuongle1206/osdcap
공식 코드Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos
https://github.com/cure-lab/DeciWatch
공식 코드DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation
https://github.com/cure-lab/SmoothNet
공식 코드SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
https://github.com/cv-core/MIT-Driverless-CV-TrainingInfra
공식 코드https://github.com/cvg/NoPoSplat
공식 코드No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.