Popular GitHub Repositories for Coco Dataset

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

(Pretrained weights provided) EfficientDet: Scalable and Efficient Object Detection implementation by Signatrix GmbH

Multi-person Human Pose Estimation with HRNet in Pytorch

Pytorch implementation of "AutoAssign: Differentiable Label Assignment for Dense Object Detection"

? Codalab-Microsoft-COCO-Image-Captioning-Challenge 3rd place solution(06.30.21)

Classifying Forged vs Authentic using Domain Adaptation across in new domains in unsupervised settings

Detect Credit card number using Mask RCNN and make task easier for OCR to retrive number from the card

fine-tuning of the Segment-Anything model by MetaAI

Fine-tuning an encoder-decoder transformer (ViT-Base-Patch16-224-In21k and DistilGPT2) for image captioning on the COCO dataset

Image Captioning with COCO Dataset

This project demonstrates an image captioning model using a Transformer architecture. The model takes an image as input and generates a descriptive caption. We use the COCO dataset for training and evaluation.

This is the code used for my project NavAssist, a smart navigational assistive device to help the visually-impaired navigate unfamiliar spaces. It uses Tensorflow lite and the COCO dataset. You will need to download labels from the COCO website. You can recreate the prototype by following the visuals at the link below. I'm running out so goodluck!

Decoding the Learned Features of Masked Autoencoders in Semantic Segmentation Tasks

Dataset of 4,368 AI-generated images based on COCO for assessing coherence and realism in synthetic imagery.

Images and video restoration in multiple-stages using MIRNETv2 model, additionally object detection on images and video through FASTER-RCNN . And complete web application in flask including responsive front-end