Papers with Code 아카이브
3D Human Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pixelite1201/agora_evaluation
공식 코드AGORA: Avatars in Geography Optimized for Regression Analysis
https://github.com/sanghunhan92/2k2k
공식 코드High-fidelity 3D Human Digitization from Single 2K Resolution Images
https://github.com/shunsukesaito/SCANimate
공식 코드SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks
https://github.com/skhu101/humangif
공식 코드https://github.com/skhu101/sherf
공식 코드https://github.com/tkz24589/SketchBodyNet
공식 코드SketchBodyNet: A Sketch-Driven Multi-faceted Decoder Network for 3D Human Reconstruction
https://github.com/vchoutas/expose
공식 코드Monocular Expressive Body Regression through Body-Driven Attention
https://github.com/vchoutas/smplify-x
공식 코드Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
https://github.com/xiaoming-zhao/oplanes
공식 코드https://github.com/xiexh20/CHORE
공식 코드CHORE: Contact, Human and Object REconstruction from a single RGB image
https://github.com/xiexh20/behave-dataset
공식 코드BEHAVE: Dataset and Method for Tracking Human Object Interactions
https://github.com/xuchen-ethz/SNARF
공식 코드SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes
https://github.com/yasaminjafarian/HDNet_TikTok
공식 코드Self-supervised 3D Representation Learning of Dressed Humans from Social Media Videos
https://github.com/yuliangxiu/icon
공식 코드https://github.com/yztang4/hap
공식 코드Human as Points: Explicit Point-based 3D Human Reconstruction from Single-view RGB Images
https://github.com/zengwang430521/DecoMR
공식 코드https://github.com/Droliven/pymaf_reimplementation
PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop
https://github.com/Jeff-sjtu/HybrIK
HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-body Mesh Recovery
https://github.com/JiangWenPL/multiperson
Coherent Reconstruction of Multiple Humans from a Single Image
https://github.com/agnJason/RGB-D-PIFuHD
PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
https://github.com/bharat-b7/IPNet
Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction
https://github.com/cardboard-q/pifuhd_demo_model_test
PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
https://github.com/chenshuang-zhang/imagenet_d
https://github.com/chingswy/HumanPoseMemo
https://github.com/huochf/StackFLOW
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
https://github.com/jeffffffli/HybrIK
HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-body Mesh Recovery
https://github.com/jiean001/models_m/tree/main/DecoMR
https://github.com/naver/posebert
https://github.com/open-mmlab/mmpose
SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
https://github.com/otaheri/GOAL
https://github.com/shunsukesaito/PIFu
PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
https://github.com/tingtingliao/mvphuman
SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks
https://github.com/wqyin/smplest-x
SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
https://github.com/xiuyu0000/new_papers_codes/tree/main/DecoMR
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.