Papers with Code 아카이브
3D Absolute Human Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 3
- 보존된 평가 기록
- 6
This task aims to solve absolute (camera-centric not root-relative) 3D human pose estimation.
<span style="color:grey; opacity: 0.6">( Image credit: RootNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/uuembodiedsocialai/FaceDiffuser
공식 코드FaceDiffuser: Speech-Driven 3D Facial Animation Synthesis Using Diffusion
https://github.com/vb000/neuricam
공식 코드NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT Cameras
https://github.com/w-shuoyan/evenhancer
공식 코드https://github.com/wuhaozhe/audio2face_mm2023
공식 코드Speech-Driven 3D Face Animation with Composite and Regional Facial Movements
https://github.com/xiaogang00/dp3df
공식 코드https://github.com/xinntao/EDVR
공식 코드EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
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/xpixelgroup/rethinkvsralignment
공식 코드https://github.com/xtudbxk/tmp
공식 코드TMP: Temporal Motion Propagation for Online Video Super-Resolution
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/yanghb22-fdu/hi3d-official
공식 코드Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Models
https://github.com/yangzhou12/ncrl
공식 코드None Class Ranking Loss for Document-Level Relation Extraction
https://github.com/yc4ny/SVAD
공식 코드https://github.com/yhw-yhw/talkshow
공식 코드https://github.com/yiranran/Audio-driven-TalkingFace-HeadPose
공식 코드Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose
https://github.com/yisuanwang/idea23d
공식 코드Idea23D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs
https://github.com/yuehan717/realviformer
공식 코드RealViformer: Investigating Attention for Real-World Video Super-Resolution
https://github.com/yuezijie/stinet-space-time-video-super-resolution
공식 코드Enhancing Space-time Video Super-resolution via Spatial-temporal Feature Interaction
https://github.com/yuliangxiu/icon
공식 코드https://github.com/yumingj/C2-Matching
공식 코드Reference-based Image and Video Super-Resolution via C2-Matching
https://github.com/yunfanLu/INR-Event-VSR
공식 코드Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolution
https://github.com/yunfanlu/hr-inr
공식 코드HR-INR: Continuous Space-Time Video Super-Resolution via Event Camera
https://github.com/yuqiao0303/fancy123
공식 코드Fancy123: One Image to High-Quality 3D Mesh Generation via Plug-and-Play Deformation
https://github.com/yxymessi/dtc123
공식 코드Diffusion Time-step Curriculum for One Image to 3D Generation
https://github.com/zczcwh/gtrs
공식 코드A Lightweight Graph Transformer Network for Human Mesh Reconstruction from 2D Human Pose
https://github.com/zengbohan0217/ipdreamer
공식 코드IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
https://github.com/zhangchenxu528/FACIAL
공식 코드FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning
https://github.com/zhaorw02/FlexiDreamer
공식 코드https://github.com/zhengchen1999/dove
공식 코드DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-Resolution
https://github.com/ziangcao0312/PhysX
공식 코드https://github.com/ziniuwan/maed
공식 코드Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation
https://github.com/zj-binxia/ssl
공식 코드Structured Sparsity Learning for Efficient Video Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.