Popular GitHub Repositories for Pedestrian Intention

A selection of state-of-the-art research materials on trajectory prediction

? A curated list of Tiny Object Detection papers and related resources.

? The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!

BoT-SORT: Robust Associations Multi-Pedestrian Tracking

[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021

Code for "Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction" CVPR 2020

Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"

a collection of computer vision projects&tools. 计算机视觉方向项目和工具集合。

Simple model to Track and Re-identify individuals in different cameras/videos.(Yolov3 & Yolov4)

The code of the Object Counting API, implemented with the YOLO algorithm and with the SORT algorithm

[ICRA 2023] Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

Annotation data for JAAD (Joint Attention in Autonomous Driving) Dataset

Deep learning based object tracking with line crossing and area intrusion detection

SARL*: Deep RL based human-aware navigation for mobile robot in crowded indoor environments implemented in ROS.

[OpenPAR] An open-source framework for Pedestrian Attribute Recognition, based on PyTorch

Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs (CVPR 2019)

A PyTorch Detectron codebase for domain adaptation of object detectors.

Flacuna was developed by fine-tuning Vicuna on Flan-mini, a comprehensive instruction collection encompassing various tasks. Vicuna is already an excellent writing assistant, and the intention behind Flacuna was to enhance Vicuna's problem-solving capabilities. To achieve this, we curated a dedicated instruction dataset called Flan-mini.

Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd.

Learning multi-agent robotic mobile manipulation with deep reinforcement learning