Fetching the paper…
Reading the bibliography…
This paper is on Few-Shot Object Detection (FSOD), where given a few templates (examples) depicting a novel class (not seen during training), the goal is to detect all of its occurrences within a set of images.
On the momentum term in gradient descent learning algorithms
Ning Qian · 1999
Earlier work this paper cites.
The pascal visual object classes (VOC) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
Selective search for object recognition
Jasper RR Uijlings, Koen EA Van De Sande, Theo Gevers, and Arnold WM Smeulders · 2013
Earlier work this paper cites.
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
Earlier work this paper cites.
The Pascal Visual Object Classes Challenge: A Retrospective
Mark Everingham, S. M. Eslami, Luc Gool, Christopher K. Williams, John Winn, and Andrew Zisserman · 2015
Earlier work this paper cites.
Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
SSD: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg · 2016
Earlier work this paper cites.
You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Earlier work this paper cites.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Earlier work this paper cites.
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Earlier work this paper cites.
Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
Earlier work this paper cites.
Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Cascade R-CNN: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
Earlier work this paper cites.
Cornernet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 2018
Earlier work this paper cites.
Generating classification weights with GNN denoising autoencoders for few-shot learning
Spyros Gidaris and Nikos Komodakis · 2019
Earlier work this paper cites.
One-shot object detection with co-attention and co-excitation
Ting-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen, and Tyng-Luh Liu · 2019
Earlier work this paper cites.
Few-shot object detection via feature reweighting
Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, and Trevor Darrell · 2019
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2019
Cited alongside, same era.
Generalized intersection over union: A metric and a loss for bounding box regression
Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian Reid, and Silvio Savarese · 2019
Cited alongside, same era.
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
Cited alongside, same era.
FCOS: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
Cited alongside, same era.
Beyond max-margin: Class margin equilibrium for few-shot object detection
Bohao Li, Boyu Yang, Chang Liu, Feng Liu, Rongrong Ji, and Qixiang Ye · 2021
Later among the works it cites.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2021
Later among the works it cites.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Later among the works it cites.
Conditional DETR for fast training convergence
Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, and Jingdong Wang · 2021
Later among the works it cites.
DeFRCN: Decoupled Faster R-CNN for few-shot object detection
Limeng Qiao, Yuxuan Zhao, Zhiyuan Li, Xi Qiu, Jianan Wu, and Chi Zhang · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Meta-learning to detect rare objects
Yu-Xiong Wang, Deva Ramanan, and Martial Hebert · 2019
Cited alongside, same era.
Meta R-CNN: Towards general solver for instance-level low-shot learning
Xiaopeng Yan, Ziliang Chen, Anni Xu, Xiaoxi Wang, Xiaodan Liang, and Liang Lin · 2019
Cited alongside, same era.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Few-shot object detection with attention-RPN and multi-relation detector
Qi Fan, Wei Zhuo, Chi-Keung Tang, and Yu-Wing Tai · 2020
Cited alongside, same era.
FSCE: Few-shot object detection via contrastive proposal encoding
Bo Sun, Banghuai Li, Shengcai Cai, Ye Yuan, and Chi Zhang · 2021
Later among the works it cites.
Universal-prototype enhancing for few-shot object detection
Aming Wu, Yahong Han, Linchao Zhu, and Yi Yang · 2021
Later among the works it cites.
Hallucination improves few-shot object detection
Weilin Zhang and Yu-Xiong Wang · 2021
Later among the works it cites.
Semantic relation reasoning for shot-stable few-shot object detection
Chenchen Zhu, Fangyi Chen, Uzair Ahmed, Zhiqiang Shen, and Marios Savvides · 2021
Later among the works it cites.
Deformable DETR: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
Later among the works it cites.
Detreg: Unsupervised pretraining with region priors for object detection
Amir Bar, Xin Wang, Vadim Kantorov, Colorado J Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, and Amir Globerson · 2022
Closest in time.
Few-shot object detection with model calibration
Qi Fan, Wei Zhuo, Chi-Keung Tang, and Yu-Wing Tai · 2022
Closest in time.
Meta faster R-CNN: Towards accurate few-shot object detection with attentive feature alignment
Guangxing Han, Shiyuan Huang, Jiawei Ma, Yicheng He, and Shih-Fu Chang · 2022
Closest in time.
Few-shot object detection with fully cross-transformer
Guangxing Han, Jiawei Ma, Shiyuan Huang, Long Chen, and Shih-Fu Chang · 2022
Closest in time.
Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim · 2022
Closest in time.
tSF: Transformer-Based Semantic Filter for Few-Shot Learning
Jinxiang Lai, Siqian Yang, Wenlong Liu, Yi Zeng, Zhongyi Huang, Wenlong Wu, Jun Liu, Bin-Bin Gao, and Chengjie Wang · 2022
Closest in time.
Airdet: Few-shot detection without fine-tuning for autonomous exploration
Bowen Li, Chen Wang, Pranay Reddy, Seungchan Kim, and Sebastian Scherer · 2022
Closest in time.
Meta-detr: Image-level few-shot detection with inter-class correlation exploitation
Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, and Eric P Xing · 2022
Closest in time.
Time-rEversed diffusioN tEnsor Transformer: A New TENET of Few-Shot Object Detection
Shan Zhang, Naila Murray, Lei Wang, and Piotr Koniusz · 2022
Closest in time.
Kernelized few-shot object detection with efficient integral aggregation
Shan Zhang, Lei Wang, Naila Murray, and Piotr Koniusz · 2022
Closest in time.