https://github.com/zhipeixu/fakeshield
AvatarShield: Visual Reinforcement Learning for Human-Centric Video Forgery Detection
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zhipeng-wei/Heuristic_black_box_adversarial_attack_on_video_recognition_models
Heuristic Black-box Adversarial Attacks on Video Recognition Models
https://github.com/zhiqiang00/Hon-GCN
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/zhoubolei/TRN-pytorch
https://github.com/zhoubolei/moments_models
Moments in Time Dataset: one million videos for event understanding
https://github.com/zhuangshaobin/Video-GPT
https://github.com/zhusiling/EDSR
https://github.com/zhusiling/EDVR
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/zhusiling/TecoGAN
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/zibojia/rslad
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/ziqi-zhang/3D-ResNets-PyTorch
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?
https://github.com/ziwei-zheng/nullu
Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicity
https://github.com/zixuan-chen/M3VOS_Experiment
M$^3$-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation
https://github.com/ziyangwang007/mamba-unet
https://github.com/zjfheart/Friendly-Adversarial-Training
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/zjsong/sspl
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/zkisthebest/Siamese-RPN
https://github.com/zllrunning/SiameseX.PyTorch
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
https://github.com/zqzqz/AdvTrajectoryPrediction
GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving
https://github.com/zrl4836/tensorflow_octConv
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
https://github.com/zswang666/Omni-CNN
https://github.com/zwtu/TokShift-Transformer-Paddle
https://github.com/zwx8981/tcsvt-2022-bvqa
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perception
https://github.com/zxhhh97/ABot
https://github.com/zzy-zhou/renet
Event-Free Moving Object Segmentation from Moving Ego Vehicle
https://github.com/zzy123abc/BSN-boundary-sensitive-network-master
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
https://github.com/zzz2010/starganv2_paddle
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://gitlab.com/birder/birder
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://gitlab.com/grounded-sport-convai/goal-baselines
HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training
https://gitlab.com/williamsdaniel888/valma
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://huggingface.co/spaces/DFisch/Image-Manipulation-Detection
DF-Net: The Digital Forensics Network for Image Forgery Detection
https://zenodo.org/record/8142658
DF-Net: The Digital Forensics Network for Image Forgery Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.