777 citations · 1.3k across the 5 of their papers we have counts for
5 papers
DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
Shilong Liu, Yaoyuan Liang, Feng Li +5
In this paper, we study the problem of visual grounding by considering both phrase extraction and grounding (PEG). In contrast to the previous phrase-known-at-test setting, PEG req…
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
Hao Zhang, Feng Li, Shilong Liu +5
We present DINO (\textbf{D}ETR with \textbf{I}mproved de\textbf{N}oising anch\textbf{O}r boxes), a state-of-the-art end-to-end object detector. % in this paper. DINO improves over…
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR
Shilong Liu, Feng Li, Hao Zhang +5
We present in this paper a novel query formulation using dynamic anchor boxes for DETR (DEtection TRansformer) and offer a deeper understanding of the role of queries in DETR. This…
Query2Label: A Simple Transformer Way to Multi-Label Classification
Shilong Liu, Lei Zhang, Xiao Yang +2
This paper presents a simple and effective approach to solving the multi-label classification problem. The proposed approach leverages Transformer decoders to query the existence o…
Unsupervised Part Segmentation through Disentangling Appearance and Shape
Shilong Liu, Lei Zhang, Xiao Yang +2
We study the problem of unsupervised discovery and segmentation of object parts, which, as an intermediate local representation, are capable of finding intrinsic object structure a…