May 20, 2024 · To this end, we introduce a strong DETR-based detector named Domain Adaptive detection TRansformer (DATR) for unsupervised domain adaptation of object detection.

This repository contains the implementation accompanying our paper DATR: Unsupervised Domain Adaptive Detection Transformer with Dataset-Level Adaptation and Prototypical Alignment.

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DATR enhances both the global representation and inter-class discriminability in the resultant feature space by utilizing our Dataset-level Alignment Scheme (DAS).

DATR is a language for lexical knowledge representation. [1] The lexical knowledge is encoded in a network of nodes. Each node has a set of attributes encoded with it. A node can represent a word or a word form.

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It is observed that DATR achieves the highest accuracy, with a mAP of percent 66.3 66.3\% 66.3 %, and shows significant improvements over previous work. The experiments demonstrate DATR’s powerful capability in addressing single-category cross-domain detection tasks.

DAT One biedt toegang tot laadborden, marktanalyses en laadtarieven voor vervoerders, makelaars en verladers.

DATR: Domain Agnostic Text Recognizer Kunal Purkayastha1,3, Shashwat Sarkar1, Shivakumara Palaiahnakote2(B), Umapada Pal1, and Palash Ghosal3 Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India [email protected] School of Science, Engineering and Environment, University of Salford, Manchester, UK