choodly

conv-social-pooling

Code for model proposed in: Nachiket Deo and Mohan M. Trivedi,"Convolutional Social Pooling for Vehicle Trajectory Prediction." CVPRW, 2018

convnet-burden

Memory consumption and FLOP count estimates for convnets

deep-person-reid

Pytorch implementation of deep person re-identification models.

DeepCC

Multi-Target, Multi-Camera Tracking

DenseDepth

High Quality Monocular Depth Estimation via Transfer Learning

Embedding-Network

Embedding network for vehicle Re-identification

KITTI-distance-estimation

Estimating distance to objects in the scene using detection information

Mask-YOLO

Inspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.

Multimodal-Image-Retrieval

Explores early fusion and late fusion approaches for Multimodal medical Image Retrieval

SEG-YOLO

Real time instance segmentation using YOLOv3 and FCN

choodly/RODNet

RODNet: Radar object detection network

choodly/Build_Week_2

choodly/Cell-DETR

Official and maintained implementation of the paper Attention-Based Transformers for Instance Segmentation of Cells in Microstructures [BIBM 2020].

choodly/centernet-inst

A little experiment combining Centernet and SOLOv2.

choodly/darts

A python library for easy manipulation and forecasting of time series.

choodly/deeplearning_registration_IR_RGB_video

choodly/Detectron2-Train-a-Instance-Segmentation-Model

Learn how to train a custom instance segmentation model with Detectron2

choodly/FineEdu-Dataset

A Fine-grained Class Students Behavior Understanding Dataset with Jointly Action and Attention Annotations

choodly/imagefusion-nestfuse

NestFuse (IEEE TIM 2020)- Pytorch >= 0.4.1

choodly/learner-performance-prediction

Simple and performant implementations of learner performance prediction algorithms.

choodly/Msnhnet

A mini pytorch inference framework which inspired from darknet.

choodly/MsnhnetSharp

C# wrapper for msnhnet.

choodly/nanonets_object_tracking

choodly/PaddlePaddle_yolact

yolact完美复刻版（paddle实现），飞桨论文复现挑战赛参赛作品

choodly/panoptic-deeplab

This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)

choodly/pig-instance-segmentation

This is the implementation code of our paper named Dual Attention-guided Feature Pyramid Network for Instance Segmentation of Group Pigs (Under Reviewer)

choodly/pykt-toolkit

pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models

choodly/RGB-Thermal-Tracking-Paper-List

Paper collection of rgb-infrared tracking algorithms.

choodly/rpi-urban-mobility-tracker

The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.

choodly/RTFNet

RGB-Thermal Fusion Network for Semantic Segmentation of Urban Scenes

choodly/SE4050-Improving-Student-Academic-Performance-Prediction-and-Intervention

This is a Project for final year Deep learning module. This project aims to address this critical issue by developing a machine learning model for predicting student academic performance and providing personalized recommendations for interventions.

choodly/tinyml-papers-and-projects

This is a list of interesting papers and projects about TinyML.

choodly/Trans2Seg

choodly/transformer

Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

choodly/transformer-time-series-prediction

proof of concept for a transformer-based time series prediction model

choodly/transfuser

[CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

choodly/Vehicle-Detection-and-Tracking-using-YOLOv3-and-Deep-Sort

I have used YOLOv3 Algorithm for Vehicle Detection and Deep Sort Algorithm for Vehicle Tracking. After tracking the vehicles I have tried counting the number of vehicles in each lane. This will help us in real life implementations like Toll Booths(To cross check the collection) and Traffic Lanes Rules Monitoring(To check if heavy vehicles are following the proper lanes or not).

choodly/VIFB

Visible and Infrared Image Fusion Benchmark

choodly/YOLO-Multi-Backbones-Attention

Model Compression—YOLOv3 with multi lightweight backbones(ShuffleNetV2 HuaWei GhostNet), attention, prune and quantization

choodly/yolov4-deepsort

Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.