Helper for dealing with MS-COCO annotations
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Updated
Sep 4, 2024 - Python
Helper for dealing with MS-COCO annotations
[IJCAI 2022] Official Pytorch code for paper “S2 Transformer for Image Captioning”
Course project for COMP 6130 Data Mining, Summer'24, Auburn University
PyTorch implementation of Conditional Generative Adversarial Networks (cGAN) for image colorization of the MS COCO dataset
Using Fast KNN for an image captioning task
NeuSyRE: A Neuro-Symbolic Visual Understanding and Reasoning Framework based on Scene Graph Enrichment
[AAAI 2024] Official code for "Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection"
[AAAI 2024] Official code for "Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection"
Reproduction of LaVisE: Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention
A PyTorch implementation of the paper: Specifying Object Attributes and Relations in Interactive Scene Generation
[ICCV '21] In this repository you find the code to our paper "Keypoint Communities".
Compact Image Captioning (CoCA) is an open source image captioning project to promote Green Computer Vision, as well as to make image captioning research accessible to universities, research labs and individual practitioners with limited financial resources.
Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629
Fast and accurate Human Pose Estimation using ShelfNet with PyTorch
Python codes to implement DeMix, a DETR assisted CutMix method for image data augmentation
SacreEOS experiments
Multi-Auto-Annotate : Automatically annotate multiple labels in your entire image directory by a single command. Works with COCO dataset and also has the ability to train on custom dataset.
[TIP] Learning to Discover Multi-Class Attentional Regions for Multi-Label Image Recognition
[CVPR 2022] Official Pytorch code for OW-DETR: Open-world Detection Transformer
Convert segmentation RGB mask images to COCO JSON format
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