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/donydchen/mvsplat
공식 코드MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images
https://github.com/ephemeral182/empirical-study-of-gpt-4o-image-gen
공식 코드https://github.com/esw0116/DynaVSR
공식 코드https://github.com/eugenelet/crfp
공식 코드Cross-Resolution Flow Propagation for Foveated Video Super-Resolution
https://github.com/eunjnnn/bfstvsr
공식 코드https://github.com/eyalnaor/DeepTemporalSR
공식 코드Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning
https://github.com/facebookresearch/meshtalk
공식 코드MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement
https://github.com/facebookresearch/pifuhd
공식 코드PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
https://github.com/fcongrui/3dattgan
공식 코드https://github.com/fedenoce/s2l-s2d
공식 코드Learning Landmarks Motion from Speech for Speaker-Agnostic 3D Talking Heads Generation
https://github.com/fudan-zvg/efficient4d
공식 코드Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Video
https://github.com/galib360/facexhubert
공식 코드https://github.com/google-research/google-research
공식 코드https://github.com/google-research/google-research/tree/master/comisr
공식 코드https://github.com/guochengqian/magic123
공식 코드Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
https://github.com/guosheng/refinenet
공식 코드RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/h-deep/trans-svsr
공식 코드A New Dataset and Transformer for Stereoscopic Video Super-Resolution
https://github.com/hitrainer/eavsr
공식 코드Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution
https://github.com/hkchengrex/XMem
공식 코드XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
https://github.com/house-leo/cfdvsr
공식 코드Collaborative Feedback Discriminative Propagation for Video Super-Resolution
https://github.com/house-leo/ctun
공식 코드Cascaded Temporal Updating Network for Efficient Video Super-Resolution
https://github.com/hyhsimon/boosted-vsr
공식 코드Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization
https://github.com/iGame-Lab/LASOR
공식 코드https://github.com/ianyeung/mgld-vsr
공식 코드Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution
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/jfzhang95/BMP
공식 코드https://github.com/jiangsutx/SPMC_VideoSR
공식 코드https://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 코드https://github.com/jiy173/MANA
공식 코드Memory-Augmented Non-Local Attention for Video Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.