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ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers

ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers

Achin Jain
Kibok Lee
Gurumurthy Swaminathan
Han Yang
Bernt Schiele
Avinash Ravichandran
O. Dabeer
    ViT
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Papers citing "ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers"

3 / 3 papers shown
Title
UFO$^2$: A Unified Framework towards Omni-supervised Object Detection
UFO2^2: A Unified Framework towards Omni-supervised Object Detection
Zhongzheng Ren
Zhiding Yu
Xiaodong Yang
Ming-Yu Liu
A. Schwing
Jan Kautz
ObjD
193
35
0
21 Oct 2020
Solving Missing-Annotation Object Detection with Background Recalibration Loss
Solving Missing-Annotation Object Detection with Background Recalibration Loss
Han Zhang
Fangyi Chen
Zhiqiang Shen
Qiqi Hao
Chenchen Zhu
Marios Savvides
ObjD
135
52
0
12 Feb 2020
CrowdHuman: A Benchmark for Detecting Human in a Crowd
CrowdHuman: A Benchmark for Detecting Human in a Crowd
Shuai Shao
Zijian Zhao
Boxun Li
Tete Xiao
Gang Yu
Xiangyu Zhang
Jian-jun Sun
222
675
0
30 Apr 2018