COCOA: Semantic Amodal Segmentation for huggingface datasets
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Updated
Sep 16, 2023 - Python
COCOA: Semantic Amodal Segmentation for huggingface datasets
A simple Python API (built on top of TensorFlow) for neural image captioning with MSCOCO data.
Encoder-Decoder CNN-LSTM Model with an attention mechanism for image captioning. Trained using the Microsoft COCO Dataset.
COCO-Stuff dataset for huggingface datasets
PyTorch implementation of SSD: Single Shot MultiBox Detector.
Microsoft COCO: Common Objects in Context for huggingface datasets
[KDD 2024] Improving the Consistency in Cross-Lingual Cross-Modal Retrieval with 1-to-K Contrastive Learning
The Jakarnotator is an annotation tool to create your own database for instance segmentation problem.
A deep-learning object detection project pre-trained on COCO dataset
Trident Pyramid Networks for Object Detection (BMVC 2022)
FQDet: Fast-converging Query-based Detector
Object Detection Dataset Format Converter
A helper library for easily converting MSCOCO format data using the loading script of huggingface datasets.
Implementation of models in our EMNLP 2019 paper: A Logic-Driven Framework for Consistency of Neural Models
MSCOCO data format details and how to evaluate mAP with pycocotools
Show, Attend, and Tell. Modified to use on UIT-ViIC dataset.
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