https://github.com/jswati31/cuda-ghr
공식 코드CUDA-GHR: Controllable Unsupervised Domain Adaptation for Gaze and Head Redirection
Papers with Code 아카이브
1 Image, 2*2 Stitchi
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/judydnguyen/pardon-feddg
공식 코드PARDON: Privacy-Aware and Robust Federated Domain Generalization
https://github.com/junggy/housecat6d
공식 코드https://github.com/junhocho/paired-glyph-matching
공식 코드https://github.com/junjie-shentu/textual-localization
공식 코드Textual Localization: Decomposing Multi-concept Images for Subject-Driven Text-to-Image Generation
https://github.com/junjiehe96/AnyStory
공식 코드AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation
https://github.com/junkunyuan/hap
공식 코드HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception
https://github.com/junleen/RainNet
공식 코드Region-aware Adaptive Instance Normalization for Image Harmonization
https://github.com/junpan19/ETDM
공식 코드Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modeling
https://github.com/junpan19/RRN
공식 코드https://github.com/junpan19/RSDN
공식 코드Video Super-Resolution with Recurrent Structure-Detail Network
https://github.com/junpan19/VSR_TGA
공식 코드https://github.com/junshutang/3DFaceShop
공식 코드3DFaceShop: Explicitly Controllable 3D-Aware Portrait Generation
https://github.com/junting/seg2vid
공식 코드https://github.com/junwuzhang19/repaint123
공식 코드https://github.com/junyanz/CycleGAN
공식 코드Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
공식 코드Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/junyuandeng/dm-calib
공식 코드Boost 3D Reconstruction using Diffusion-based Monocular Camera Calibration
https://github.com/junzastar/dftr_voting
공식 코드https://github.com/juseonghan/meshbrush
공식 코드MeshBrush: Painting the Anatomical Mesh with Neural Stylization for Endoscopy
https://github.com/justimyhxu/grm
공식 코드GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation
https://github.com/jutanke/mv3dpose
공식 코드Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views
https://github.com/juyongchang/PoseLifter
공식 코드PoseLifter: Absolute 3D human pose lifting network from a single noisy 2D human pose
https://github.com/juzezhang/ikol
공식 코드https://github.com/jwen307/diamondintherough
공식 코드Diamond in the rough: Improving image realism by traversing the GAN latent space
https://github.com/jychen9811/doc-vton
공식 코드OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup
https://github.com/jytime/Deep-SfM-Revisited
공식 코드https://github.com/jzhao12/cvam-pose
공식 코드CVAM-Pose: Conditional Variational Autoencoder for Multi-Object Monocular Pose Estimation
https://github.com/k032131/EPOSIT
공식 코드EPOSIT: An Absolute Pose Estimation Method for Pinhole and Fish-Eye Cameras
https://github.com/k2kobayashi/crank
공식 코드https://github.com/kaichen-z/rad
공식 코드RAD: A Dataset and Benchmark for Real-Life Anomaly Detection with Robotic Observations
https://github.com/kaist-cvml-lab/scribble-diffusion
공식 코드Scribble-Guided Diffusion for Training-free Text-to-Image Generation
https://github.com/kaiyuesun98/t2i-personalization-with-ar
공식 코드Personalized Text-to-Image Generation with Auto-Regressive Models
https://github.com/kakaobrain/magvlt
공식 코드https://github.com/kakaobrain/rq-vae-transformer
공식 코드https://github.com/kamepong/StarGAN-VC
공식 코드StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.