https://github.com/ali-vilab/VGen
Composer: Creative and Controllable Image Synthesis with Composable Conditions
Papers with Code 아카이브
Virtual Try-on
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Virtual try-on of clothing or other items such as glasses and makeup. Most recent techniques use Generative Adversarial Networks.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ali-vilab/i2vgen-xl
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/ali-vilab/videocomposer
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/alibaba-yuanjing-aigclab/vivid
https://github.com/andrewjong/SwapNet
https://github.com/ankitajaiswal00/Try-First
https://github.com/arunt-sjsu/DL_Project
Toward Characteristic-Preserving Image-based Virtual Try-On Network
https://github.com/cuiaiyu/street-tryon-benchmark
Learning Garment DensePose for Robust Warping in Virtual Try-On
https://github.com/damo-vilab/videocomposer
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/fashn-AI/tryondiffusion
https://github.com/gkeng/viton-gan
VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss
https://github.com/jiayunz/Virtual-Try-On
Toward Characteristic-Preserving Image-based Virtual Try-On Network
https://github.com/jtiger958/hair-segmentation-pytorch
https://github.com/levindabhi/SieveNet
SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On
https://github.com/maria-korosteleva/Body-Shape-Estimation
Detailed, accurate, human shape estimation from clothed 3D scan sequences
https://github.com/minar09/acgpn
https://github.com/minar09/cp-vton-plus
https://github.com/ml-gsai/concat-id
Concat-ID: Towards Universal Identity-Preserving Video Synthesis
https://github.com/nile649/POLY-GAN
https://github.com/pscmap13/viton-gan
VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss
https://github.com/shinechen1024/magicclothing
OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on
https://github.com/switchablenorms/DeepFashion_Try_On
https://github.com/yangyucheng000/University/tree/main/model-3/sew_d
Towards Garment Sewing Pattern Reconstruction from a Single Image
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.