https://github.com/ianyeung/mgld-vsr
공식 코드Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution
Papers with Code 아카이브
3D Human Pose Estimation
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- 보존된 평가 기록
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3D Human Pose Estimation is a computer vision task that involves estimating the 3D positions and orientations of body joints and bones from 2D images or videos. The goal is to reconstruct the 3D pose of a person in real-time, which can be used in a variety of applications, such as virtual reality, human-computer interaction, and motion analysis.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/iballester/SPiKE
공식 코드https://github.com/icitylab/posegraf
공식 코드PoseGRAF: Geometric-Reinforced Adaptive Fusion for Monocular 3D Human Pose Estimation
https://github.com/idiap/residual_pose
공식 코드Residual Pose: A Decoupled Approach for Depth-based 3D Human Pose Estimation
https://github.com/idsia-robotics/proximity-quadrotor-learning
공식 코드Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches
https://github.com/indigopurple/efenet
공식 코드EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation
https://github.com/ipl-uw/ZeDO-Release
공식 코드Back to Optimization: Diffusion-based Zero-Shot 3D Human Pose Estimation
https://github.com/isarandi/metrabs
공식 코드MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation
https://github.com/isarandi/metro-pose3d
공식 코드Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose Estimation
https://github.com/isarandi/nlf
공식 코드Neural Localizer Fields for Continuous 3D Human Pose and Shape Estimation
https://github.com/isarandi/smplfitter
공식 코드Neural Localizer Fields for Continuous 3D Human Pose and Shape Estimation
https://github.com/isarandi/synthetic-occlusion
공식 코드https://github.com/ivalab/kgn
공식 코드KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D input
https://github.com/ivclab/Part-Aware_Measurement_for_3D_Pose_Estimation_and_Tracking
공식 코드Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking
https://github.com/jaisharmz/geocentric-pose
공식 코드A Deep Learning Ensemble Framework for Off-Nadir Geocentric Pose Prediction
https://github.com/jasonyzhang/phd
공식 코드https://github.com/jayrmh/QAERTS
공식 코드https://github.com/jeff-sjtu/dnd
공식 코드https://github.com/jeff-sjtu/niki
공식 코드https://github.com/jfzhang95/BMP
공식 코드https://github.com/jfzhang95/PoseAug
공식 코드PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation
https://github.com/jiahaoLjh/HumanDepth
공식 코드HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization
https://github.com/jiahaoLjh/PlaneSweepPose
공식 코드Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo
https://github.com/jiahaoLjh/trajectory-pose-3d
공식 코드Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation
https://github.com/jiangsutx/SPMC_VideoSR
공식 코드https://github.com/jianwang-mpi/GlobalEgoMocap
공식 코드https://github.com/jianwang-mpi/SceneEgo
공식 코드https://github.com/jihoonerd/Conditional-Motion-In-Betweening
공식 코드https://github.com/jike5/LATITUDE
공식 코드LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF
https://github.com/jimmyzou/eventhpe
공식 코드https://github.com/jimmyzou/humanposetracking_snn
공식 코드Highly Efficient 3D Human Pose Tracking from Events with Spiking Spatiotemporal Transformer
https://github.com/jingyunliang/hcflow
공식 코드Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
https://github.com/jingyunliang/rvrt
공식 코드Recurrent Video Restoration Transformer with Guided Deformable Attention
https://github.com/jingyunliang/swinir
공식 코드https://github.com/jingyunliang/vrt
공식 코드https://github.com/jinsuyoo/SSA-VSR
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.