Source code for ICASSP 2022 paper "MM-DFN: Multimodal Dynamic Fusion Network For Emotion Recognition in Conversations".

code for Image Manipulation Detection by Multi-View Multi-Scale Supervision

Official PyTorch implementation of StyleGAN3

开发者边车，github打不开，github加速，git clone加速，git release下载加速，stackoverflow加速

[CVPR2024] Official implementation of SODA-SR.

[CVPR 2023] Pytorch Implementation for CVPR2023 paper: Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection

Official code for CAT-Net: Compression Artifact Tracing Network. Image manipulation detection and localization.

TruFor

[CVPR2022] End-to-End Reconstruction-Classification Learning for Face Forgery Detection

Code for CVPR2019 Towards Natural and Accurate Future Motion Prediction of Humans and Animals

This is an official implementation of our CVPR 2021 paper "Deep Dual Consecutive Network for Human Pose Estimation" (https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Deep_Dual_Consecutive_…

Machine learning, in numpy

Adversarial Learning for Constrained Image Splicing Detection and Localization based on Atrous Convolution

OpenMMLab Detection Toolbox and Benchmark

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

All Algorithms implemented in Python

Pytorch implementation of convolutional neural network visualization techniques

convolution oriented boundaries (pytorch)

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

Code for "Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation" (CVPR 2018)

This repository contains the reference implementation for our proposed Convolutional CRFs.

Superpixel Sampling Networks (ECCV2018)

Pytorch based implemenatation of Fully Convolutional Networks

InceptionV3, InceptionV4, Inception-Resnet pretrained models for Torch7 and PyTorch

🔥🔥 A MXNet implementation of Squeeze-and-Excitation Networks (SE-ResNext, SE-Resnet, SE-Inception-v4 and SE-Inception-Resnet-v2) 🔥🔥

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.