https://github.com/rehglab/rave
RAVE: Randomized Noise Shuffling for Fast and Consistent Video Editing with Diffusion Models
Papers with Code 아카이브
Video Editing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ruoyufeng/ccedit
CCEdit: Creative and Controllable Video Editing via Diffusion Models
https://github.com/shesay-noway/Free-Form-Video-Inpainting
Free-form Video Inpainting with 3D Gated Convolution and Temporal PatchGAN
https://github.com/soccernet/sn-grounding
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
https://github.com/soccernet/sn-spotting
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
https://github.com/thiagoambiel/NeuralAtlases
https://github.com/vinthony/video-retalking
VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
https://github.com/vye16/deformable-sprites
https://github.com/yccyenchicheng/p2pvg
https://github.com/ykasten/layered-neural-atlases
https://github.com/yrcong/flatten
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing
https://github.com/zhipeixu/fakeshield
https://github.com/zswang666/Omni-CNN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.