https://github.com/Lotayou/RATE
Region-adaptive Texture Enhancement for Detailed Person Image Synthesis
Papers with Code 아카이브
Pose Transfer
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Striptease
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/TianxiangMa/MUST-GAN
MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation
https://github.com/ali-vilab/VGen
Composer: Creative and Controllable Image Synthesis with Composable Conditions
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/charliememory/Disentangled-Person-Image-Generation
https://github.com/chuanqichen/deepcoaching
https://github.com/damo-vilab/videocomposer
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/jiashunwang/ZPT
https://github.com/kzhou23/shape_pose_disent
https://github.com/ly015/intrinsic_flow
https://github.com/menyifang/adgan
Controllable Person Image Synthesis with Attribute-Decomposed GAN
https://github.com/modelscope/modelscope
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/sgoldyaev/DeepFashion.ADGAN
https://github.com/viiika/diffusion-conductor
VirtualConductor: Music-driven Conducting Video Generation System
https://github.com/zsypotter/pose_transfer_keypoint
Progressive Pose Attention Transfer for Person Image Generation
https://github.com/zycliao/skeleton-free-pose-transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.