https://github.com/vinthony/video-retalking
VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/visaVita/mmaction2
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/vita-epfl/stay-on-track
MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
https://github.com/vita-epfl/unitraj
Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction
https://github.com/vivym/OctaveConv.pytorch
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://github.com/vlievin/Unet
https://github.com/vpaliwal1/Deep_learning_SRCNN
https://github.com/vscoboy/AI-
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/vturrisi/solo-learn
https://github.com/vuanhtu1993/Keras-SRGANs
https://github.com/vwegn/dm
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vztu/BVQA_Benchmark
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
https://github.com/vztu/VIDEVAL
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
https://github.com/vztu/VIDEVAL_release
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
https://github.com/w-sugar/Video-Swin-Transformer
https://github.com/w86763777/pytorch-gan-metrics
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/w86763777/pytorch-image-generation-metrics
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/waltersimoncini/fungivision
https://github.com/walzimmer/bat-3d
https://github.com/wan2000/mc-mot
https://github.com/wanboyang/Anomaly_AR_Net_ICME_2020
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning
https://github.com/wanglichenxj/EV-Action-Electromyography-Vision-Multi-Modal-Action-Dataset
EV-Action: Electromyography-Vision Multi-Modal Action Dataset
https://github.com/wangwenxi-handsome/joint-multipathpp
https://github.com/wangxiao5791509/SiamDW_tracker_revised
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
https://github.com/wangxiao5791509/Tracking-with-Deep-Reinforcement-Learning
https://github.com/wannabeOG/ExpertNet-Pytorch
https://github.com/wasilone11/ICPR-RIP-2024
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/waterdisappear/nudt4mstar
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/watsonyanghx/GAN_Lib_Tensorflow
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/wei-tim/YOWO
https://github.com/weixuan-wang123/ReMaKE
Editing Large Language Models: Problems, Methods, and Opportunities
https://github.com/weiyangfb/PyTorchSparseGAT
https://github.com/wen227/Pokemon_Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wenbihan/vidosat_icip2015
VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video Denoising
https://github.com/wenguanwang/AGS
https://github.com/wenkaip-1836890/pyromid_l5prediction
One Thousand and One Hours: Self-driving Motion Prediction Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.