https://github.com/TotalVariation/Flattenet
공식 코드FlatteNet: A Simple Versatile Framework for Dense Pixelwise Prediction
Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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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/Totoro97/Vid2Curve
공식 코드Vid2Curve: Simultaneous Camera Motion Estimation and Thin Structure Reconstruction from an RGB Video
https://github.com/ToyotaResearchInstitute/simnet
공식 코드SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo
https://github.com/UMich-BipedLab/extrinsic_lidar_camera_calibration
공식 코드https://github.com/UMich-BipedLab/global_pose_estimation_for_optimal_shape
공식 코드https://github.com/UZ-SLAMLab/DrunkardsOdometry
공식 코드The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes
https://github.com/UditSinghParihar/RoRD
공식 코드RoRD: Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching
https://github.com/Uehwan/SimVODIS
공식 코드SimVODIS: Simultaneous Visual Odometry, Object Detection, and Instance Segmentation
https://github.com/Uehwan/VisionForPedestrian
공식 코드https://github.com/Unity-Technologies/AnthroNet
공식 코드AnthroNet: Conditional Generation of Humans via Anthropometrics
https://github.com/Unity-Technologies/com.unity.cv.synthetichumans
공식 코드AnthroNet: Conditional Generation of Humans via Anthropometrics
https://github.com/VCL3D/StructureNet
공식 코드Deep Soft Procrustes for Markerless Volumetric Sensor Alignment
https://github.com/VDIGPKU/GSTO
공식 코드GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling
https://github.com/VIS4ROB-lab/covins
공식 코드COVINS-G: A Generic Back-end for Collaborative Visual-Inertial SLAM
https://github.com/VITA-Group/NeuralLift-360
공식 코드NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views
https://github.com/VRU-intention/casr
공식 코드Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation
https://github.com/Va6lue/BST-Badminton-Stroke-type-Transformer
공식 코드BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports
https://github.com/Vchitect/LaVie
공식 코드LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models
https://github.com/Vegetebird/MHFormer
공식 코드MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
https://github.com/Vegetebird/StridedTransformer-Pose3D
공식 코드Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
https://github.com/VincentHancoder/REPARO
공식 코드REPARO: Compositional 3D Assets Generation with Differentiable 3D Layout Alignment
https://github.com/Visual-Attention-Network/VAN-Classification
공식 코드https://github.com/VisualComputingInstitute/ShapePriors_GCPR16
공식 코드https://github.com/WU-CVGL/MVControl-threestudio
공식 코드Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting
https://github.com/WU-CVGL/USB-NeRF
공식 코드USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
https://github.com/Walter0807/MotionBERT
공식 코드MotionBERT: A Unified Perspective on Learning Human Motion Representations
https://github.com/Westlake-AI/MogaNet
공식 코드https://github.com/Westlake-AI/openmixup
공식 코드https://github.com/XRIM-Lab/GS-CPR
공식 코드GSLoc: Efficient Camera Pose Refinement via 3D Gaussian Splatting
https://github.com/XinyiYing/D3Dnet
공식 코드https://github.com/Xinyu-Yi/TransPose
공식 코드TransPose: Real-time 3D Human Translation and Pose Estimation with Six Inertial Sensors
https://github.com/XiongjunGuan/JIPNet
공식 코드Joint Identity Verification and Pose Alignment for Partial Fingerprints
https://github.com/YadiraF/DECA
공식 코드Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
https://github.com/YadiraF/PIXIE
공식 코드Collaborative Regression of Expressive Bodies using Moderation
https://github.com/YangDi666/SSTA-PRS
공식 코드https://github.com/York-SDCNLab/Ghost-DeblurGAN
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.