VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Implementation of our paper - Recurrent Convolutional Network for Video-based Person Re-Identification

Faster R-CNN

Joint Detection and Identification Feature Learning for Person Search

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

Deep Feature Flow for Video Recognition

OpenPose: A Real-Time Multi-Person Keypoint Detection And Multi-Threading C++ Library

Simple Online Realtime Tracking with a Deep Association Metric

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

visual tracker benchmark results

Tensorflow based implementation of deep siamese LSTM network to capture phrase/sentence similarity using character embeddings

Metric Learning with Graph Convolutional Neural Networks

Implementation of Graph Auto-Encoders in TensorFlow

TensorFlow Tutorial and Examples for Beginners with Latest APIs

Pedestrian Alignment Network for Large-scale Person Re-identification

Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification

Pytorch implementation of the Attention-based Graph Neural Network(AGNN)

In pytorch Learing Neural Networks likes CNN、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

Super Resolution for images using deep learning.

A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)

Pytorch implement of Person re-identification baseline. We arrived Rank@1=88.24%, mAP=70.68% only with softmax loss. Re-ranking is added.

Implementation of Graph Convolutional Networks in TensorFlow

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

A python implementation of Multiple Object Tracking(MOT) evaluation toolkit(2D)

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

Graph Convolutional Networks in PyTorch

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

Sample Code for Gated Graph Neural Networks