Papers with Code 아카이브
Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 5
- 보존된 평가 기록
- 5
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/alex04072000/SingleHDR
공식 코드Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
https://github.com/andreguo/itmlut
공식 코드Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display
https://github.com/barrybarry-smith/driv3r
공식 코드Driv3R: Learning Dense 4D Reconstruction for Autonomous Driving
https://github.com/bcjuan/itmmqnet
공식 코드A Mixed Quantization Network for Computationally Efficient Mobile Inverse Tone Mapping
https://github.com/caizhongang/SMPLer-X
공식 코드SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
https://github.com/cao-cong/uncltmo
공식 코드Unsupervised HDR Image and Video Tone Mapping via Contrastive Learning
https://github.com/chenhsing/ssp3d
공식 코드Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors
https://github.com/compphoto/IntrinsicHDR
공식 코드https://github.com/continental/seed4d
공식 코드SEED4D: A Synthetic Ego--Exo Dynamic 4D Data Generator, Driving Dataset and Benchmark
https://github.com/cs-gangxu/fdan
공식 코드https://github.com/cure-lab/SmoothNet
공식 코드SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
https://github.com/cv-rits/LMSCNet
공식 코드https://github.com/cv-rits/MonoScene
공식 코드https://github.com/cvlab-columbia/zero123
공식 코드https://github.com/czq142857/implicit-decoder
공식 코드https://github.com/diegothomas/TetraTSDF
공식 코드TetraTSDF: 3D human reconstruction from a single image with a tetrahedral outer shell
https://github.com/donkeymouse/thermalchameleon
공식 코드Thermal Chameleon: Task-Adaptive Tone-mapping for Radiometric Thermal-Infrared images
https://github.com/dqj5182/contho_release
공식 코드Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer
https://github.com/envision-research/driverecon
공식 코드DrivingRecon: Large 4D Gaussian Reconstruction Model For Autonomous Driving
https://github.com/facebookresearch/AutoAvatar
공식 코드AutoAvatar: Autoregressive Neural Fields for Dynamic Avatar Modeling
https://github.com/facebookresearch/KeypointNeRF
공식 코드https://github.com/facebookresearch/frankmocap
공식 코드FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration
https://github.com/facebookresearch/mcc
공식 코드https://github.com/facebookresearch/phosa
공식 코드Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
https://github.com/facebookresearch/pifuhd
공식 코드PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization
https://github.com/fengzhang427/LLF-LUT
공식 코드Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone Mapping
https://github.com/frozenburning/text2light
공식 코드https://github.com/fudan-zvg/diffusion-square
공식 코드https://github.com/garyzhu1996/umiformer
공식 코드UMIFormer: Mining the Correlations between Similar Tokens for Multi-View 3D Reconstruction
https://github.com/gen-verse/widerange4d
공식 코드WideRange4D: Enabling High-Quality 4D Reconstruction with Wide-Range Movements and Scenes
https://github.com/google/nerfies
공식 코드https://github.com/hebing-sjtu/S4D
공식 코드S4D: Streaming 4D Real-World Reconstruction with Gaussians and 3D Control Points
https://github.com/hkust-vgd/rfnet-4d
공식 코드https://github.com/hongxiaoy/ISO
공식 코드https://github.com/hulitaotom/Joint-Multi-Scale-Tone-Mapping-and-Denoising-for-HDR-Image-Enhancement
공식 코드Joint Multi-Scale Tone Mapping and Denoising for HDR Image Enhancement
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.