https://github.com/CandleLabAI/MotionAura-ICLR-2025
공식 코드MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
Papers with Code 아카이브
Video Inpainting
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The goal of Video Inpainting is to fill in missing regions of a given video sequence with contents that are both spatially and temporally coherent. Video Inpainting, also known as video completion, has many real-world applications such as undesired object removal and video restoration.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/FrancisXZhang/DAEVI
공식 코드https://github.com/Haotianz94/IL_video_inpainting
공식 코드https://github.com/HarryHsing/Video-Instance-Shadow-Detection
공식 코드https://github.com/IRENEKO/TTC
공식 코드Fast and Accurate Tensor Completion with Total Variation Regularized Tensor Trains
https://github.com/MCG-NKU/E2FGVI
공식 코드Towards An End-to-End Framework for Flow-Guided Video Inpainting
https://github.com/MaureenZOU/TSAM
공식 코드Progressive Temporal Feature Alignment Network for Video Inpainting
https://github.com/MichiganCOG/devil
공식 코드The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting
https://github.com/Suyimu/WRV2
공식 코드Raformer: Redundancy-Aware Transformer for Video Wire Inpainting
https://github.com/TencentARC/VideoPainter
공식 코드VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control
https://github.com/Tengfei-Wang/Implicit-Internal-Video-Inpainting
공식 코드Internal Video Inpainting by Implicit Long-range Propagation
https://github.com/ali-vilab/unianimate-dit
공식 코드https://github.com/amjltc295/Free-Form-Video-Inpainting
공식 코드Free-form Video Inpainting with 3D Gated Convolution and Temporal PatchGAN
https://github.com/bernhard2202/improved-video-gan
공식 코드Improving Video Generation for Multi-functional Applications
https://github.com/bipashasen/INRV
공식 코드INR-V: A Continuous Representation Space for Video-based Generative Tasks
https://github.com/ftmghorbani/EVI-HRnet
공식 코드Expression-aware video inpainting for HMD removal in XR applications
https://github.com/haochen-rye/hnerv
공식 코드https://github.com/hitachinsk/fgt
공식 코드https://github.com/jianzongwu/language-driven-video-inpainting
공식 코드Towards Language-Driven Video Inpainting via Multimodal Large Language Models
https://github.com/kyuyeonpooh/Audio-Visual-Deep-Video-Inpainting
공식 코드Deep Video Inpainting Guided by Audio-Visual Self-Supervision
https://github.com/liutighe/bscv-dataset
공식 코드Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method
https://github.com/lixiaowen-xw/diffueraser
공식 코드https://github.com/magicffourier/vq-nerv
공식 코드VQ-NeRV: A Vector Quantized Neural Representation for Videos
https://github.com/masterhow/flowlens
공식 코드Beyond the Field-of-View: Enhancing Scene Visibility and Perception with Clip-Recurrent Transformer
https://github.com/mcahny/Deep-Video-Inpainting
공식 코드https://github.com/mcg-nju/bivdiff
공식 코드https://github.com/multimediafor/truvil
공식 코드Trusted Video Inpainting Localization via Deep Attentive Noise Learning
https://github.com/multimediafor/vilocal
공식 코드https://github.com/nbei/Deep-Flow-Guided-Video-Inpainting
공식 코드https://github.com/ncherel/infusion
공식 코드Infusion: internal diffusion for inpainting of dynamic textures and complex motion
https://github.com/nevsnev/fgdvi
공식 코드https://github.com/nivha/single_video_generation
공식 코드https://github.com/owenzlz/egohos
공식 코드Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications
https://github.com/pku-yuangroup/swapanyone
공식 코드SwapAnyone: Consistent and Realistic Video Synthesis for Swapping Any Person into Any Video
https://github.com/researchmm/STTN
공식 코드Learning Joint Spatial-Temporal Transformations for Video Inpainting
https://github.com/ruiliu-ai/DSTT
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.