ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2209.11559
  4. Cited By
Query-based Hard-Image Retrieval for Object Detection at Test Time
v1v2 (latest)

Query-based Hard-Image Retrieval for Object Detection at Test Time

23 September 2022
Edward W. Ayers
Jonathan Sadeghi
John Redford
Romain Mueller
P. Dokania
ArXiv (abs)PDFHTMLGithub (18★)

Papers citing "Query-based Hard-Image Retrieval for Object Detection at Test Time"

21 / 21 papers shown
Title
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and
  Out Distribution Robustness
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness
Francesco Pinto
Harry Yang
Ser-Nam Lim
Philip Torr
P. Dokania
UQCV
81
36
0
29 Jun 2022
Active Learning for Deep Object Detection via Probabilistic Modeling
Active Learning for Deep Object Detection via Probabilistic Modeling
Jiwoong Choi
Ismail Elezi
Hyuk-Jae Lee
C. Farabet
J. Álvarez
62
123
0
30 Mar 2021
Consistency-based Active Learning for Object Detection
Consistency-based Active Learning for Object Detection
Weiping Yu
Sijie Zhu
Taojiannan Yang
Chong Chen
ObjD
48
51
0
18 Mar 2021
Estimating and Evaluating Regression Predictive Uncertainty in Deep
  Object Detectors
Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors
Ali Harakeh
Steven L. Waslander
UQCV
100
41
0
13 Jan 2021
Simple and Principled Uncertainty Estimation with Deterministic Deep
  Learning via Distance Awareness
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCVBDL
171
451
0
17 Jun 2020
Scalable Active Learning for Object Detection
Scalable Active Learning for Object Detection
Elmar Haussmann
Michele Fenzi
Kashyap Chitta
J. Ivanecký
Hanson Xu
D. Roy
Akshita Mittel
Nicolas Koumchatzky
C. Farabet
J. Álvarez
44
110
0
09 Apr 2020
Calibrating Deep Neural Networks using Focal Loss
Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti
Viveka Kulharia
Amartya Sanyal
Stuart Golodetz
Philip Torr
P. Dokania
UQCV
81
463
0
21 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
511
42,449
0
03 Dec 2019
Active Learning for Deep Detection Neural Networks
Active Learning for Deep Detection Neural Networks
H. H. Aghdam
Abel Gonzalez-Garcia
Joost van de Weijer
Antonio M. López
VLMObjD
87
139
0
20 Nov 2019
Cascade R-CNN: High Quality Object Detection and Instance Segmentation
Cascade R-CNN: High Quality Object Detection and Instance Segmentation
Zhaowei Cai
Nuno Vasconcelos
ObjD
79
1,356
0
24 Jun 2019
MMDetection: Open MMLab Detection Toolbox and Benchmark
MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai-xiang Chen
Jiaqi Wang
Jiangmiao Pang
Yuhang Cao
Yu Xiong
...
Jingdong Wang
Jianping Shi
Wanli Ouyang
Chen Change Loy
Dahua Lin
VOS
153
2,868
0
17 Jun 2019
Libra R-CNN: Towards Balanced Learning for Object Detection
Libra R-CNN: Towards Balanced Learning for Object Detection
Jiangmiao Pang
Kai-xiang Chen
Jianping Shi
H. Feng
Wanli Ouyang
Dahua Lin
ObjD
81
1,294
0
04 Apr 2019
nuScenes: A multimodal dataset for autonomous driving
nuScenes: A multimodal dataset for autonomous driving
Holger Caesar
Varun Bankiti
Alex H. Lang
Sourabh Vora
Venice Erin Liong
Qiang Xu
Anush Krishnan
Yuxin Pan
G. Baldan
Oscar Beijbom
3DPC
298
5,739
0
26 Mar 2019
Deep Active Learning for Efficient Training of a LiDAR 3D Object
  Detector
Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector
Di Feng
Xiao Wei
Lars Rosenbaum
A. Maki
Klaus C. J. Dietmayer
3DPC
58
86
0
29 Jan 2019
Evidential Deep Learning to Quantify Classification Uncertainty
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy
Lance M. Kaplan
M. Kandemir
OODUQCVEDLBDL
182
996
0
05 Jun 2018
Mask R-CNN
Mask R-CNN
Kaiming He
Georgia Gkioxari
Piotr Dollár
Ross B. Girshick
ObjD
352
27,195
0
20 Mar 2017
Deep Bayesian Active Learning with Image Data
Deep Bayesian Active Learning with Image Data
Y. Gal
Riashat Islam
Zoubin Ghahramani
BDLUQCV
70
1,735
0
08 Mar 2017
Hard Negative Mining for Metric Learning Based Zero-Shot Classification
Hard Negative Mining for Metric Learning Based Zero-Shot Classification
Max Bucher
Stéphane Herbin
F. Jurie
32
57
0
26 Aug 2016
Training Region-based Object Detectors with Online Hard Example Mining
Training Region-based Object Detectors with Online Hard Example Mining
Abhinav Shrivastava
Abhinav Gupta
Ross B. Girshick
ObjD
151
2,418
0
12 Apr 2016
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
  Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren
Kaiming He
Ross B. Girshick
Jian Sun
AIMatObjD
520
62,294
0
04 Jun 2015
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
413
43,667
0
01 May 2014
1