https://github.com/nysp78/counterfactual-video-generation
공식 코드Causally Steered Diffusion for Automated Video Counterfactual Generation
Papers with Code 아카이브
Video Editing
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/omerbt/Text2LIVE
공식 코드https://github.com/pardoalejo/moviecuts
공식 코드MovieCuts: A New Dataset and Benchmark for Cut Type Recognition
https://github.com/phoenix104104/fast_blind_video_consistency
공식 코드https://github.com/picsart-ai-research/text2video-zero
공식 코드Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators
https://github.com/rehg-lab/rave
공식 코드RAVE: Randomized Noise Shuffling for Fast and Consistent Video Editing with Diffusion Models
https://github.com/rese1f/stablevideo
공식 코드StableVideo: Text-driven Consistency-aware Diffusion Video Editing
https://github.com/rickyskywalker/dragvideo-official
공식 코드https://github.com/runwayml/guided-inpainting
공식 코드https://github.com/salesforce/lavis
공식 코드Moonshot: Towards Controllable Video Generation and Editing with Multimodal Conditions
https://github.com/samchen2003/editboard
공식 코드EditBoard: Towards a Comprehensive Evaluation Benchmark for Text-Based Video Editing Models
https://github.com/showlab/loveu-tgve-2023
공식 코드https://github.com/singlezombie/afldm
공식 코드Alias-Free Latent Diffusion Models:Improving Fractional Shift Equivariance of Diffusion Latent Space
https://github.com/sunxm2357/TAI_video_frame_inpainting
공식 코드A Temporally-Aware Interpolation Network for Video Frame Inpainting
https://github.com/tanvir-utexas/adave
공식 코드Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior
https://github.com/tencentarc/ditctrl
공식 코드https://github.com/thu-ml/controlvideo
공식 코드ControlVideo: Conditional Control for One-shot Text-driven Video Editing and Beyond
https://github.com/tiger-ai-lab/anyv2v
공식 코드AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks
https://github.com/tonniia/zero2hero
공식 코드Zero-to-Hero: Zero-Shot Initialization Empowering Reference-Based Video Appearance Editing
https://github.com/vahidzee/ennelut
공식 코드Efficient Neural Network Encoding for 3D Color Lookup Tables
https://github.com/wan-video/wan2.1
공식 코드https://github.com/wangjiangshan0725/cove
공식 코드COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing
https://github.com/wangjiangshan0725/rf-solver-edit
공식 코드https://github.com/weifeng-chen/control-a-video
공식 코드https://github.com/weihaox/dynode_released
공식 코드https://github.com/wenhao728/awesome-diffusion-v2v
공식 코드https://github.com/whq-xxh/rvsd
공식 코드https://github.com/wilson1yan/povt
공식 코드Patch-based Object-centric Transformers for Efficient Video Generation
https://github.com/wyhsirius/LEO
공식 코드LEO: Generative Latent Image Animator for Human Video Synthesis
https://github.com/xinchengshuai/awesome-image-editing
공식 코드A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models
https://github.com/xw-hu/unveiling-deep-shadows
공식 코드https://github.com/yangling0818/contextdiff
공식 코드Contextualized Diffusion Models for Text-Guided Image and Video Generation
https://github.com/yudianzheng/sketchvideo
공식 코드https://github.com/yunlong10/ads-1k
공식 코드Multi-modal Segment Assemblage Network for Ad Video Editing with Importance-Coherence Reward
https://github.com/yuval-alaluf/stylegan3-editing
공식 코드Third Time's the Charm? Image and Video Editing with StyleGAN3
https://github.com/yvanliang/DriveEditor
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.