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Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training.
Algorithm as 136: A k-means clustering algorithm
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Andrew Ng, Michael Jordan, and Yair Weiss · 2001
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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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
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The pascal visual object classes challenge: A retrospective
Mark Everingham, SM Ali Eslami, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2016
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Yolo9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Few-shot object detection via feature reweighting
Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, and Trevor Darrell · 2019
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Basnet: Boundary-aware salient object detection
Xuebin Qin, Zichen Zhang, Chenyang Huang, Chao Gao, Masood Dehghan, and Martin Jagersand · 2019
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Meta-learning to detect rare objects
Yu-Xiong Wang, Deva Ramanan, and Martial Hebert · 2019
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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
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Few-shot object detection with attention-rpn and multi-relation detector
Qi Fan, Wei Zhuo, Chi-Keung Tang, and Yu-Wing Tai · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
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Frustratingly simple few-shot object detection
Xin Wang, Thomas E Huang, Trevor Darrell, Joseph E Gonzalez, and Fisher Yu · 2020
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Multi-scale positive sample refinement for few-shot object detection
Jiaxi Wu, Songtao Liu, Di Huang, and Yunhong Wang · 2020
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Few-shot object detection via association and discrimination
Yuhang Cao, Jiaqi Wang, Ying Jin, Tong Wu, Kai Chen, Ziwei Liu, and Dahua Lin · 2021
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Dynamic head: Unifying object detection heads with attentions
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Fsce: Few-shot object detection via contrastive proposal encoding
Bo Sun, Banghuai Li, Shengcai Cai, Ye Yuan, and Chi Zhang · 2021
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Universal-prototype enhancing for few-shot object detection
Aming Wu, Yahong Han, Linchao Zhu, and Yi Yang · 2021
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Hallucination improves few-shot object detection
Weilin Zhang and Yu-Xiong Wang · 2021
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Few-shot object detection with fully cross-transformer
Guangxing Han, Jiawei Ma, Shiyuan Huang, Long Chen, and Shih-Fu Chang · 2022
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Xiyang Dai, Yinpeng Chen, Bin Xiao, Dongdong Chen, Mengchen Liu, Lu Yuan, and Lei Zhang · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Simple copy-paste is a strong data augmentation method for instance segmentation
Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D Cubuk, Quoc V Le, and Barret Zoph · 2021
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Query adaptive few-shot object detection with heterogeneous graph convolutional networks
Guangxing Han, Yicheng He, Shiyuan Huang, Jiawei Ma, and Shih-Fu Chang · 2021
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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 · 2021
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Transformation invariant few-shot object detection
Aoxue Li and Zhenguo Li · 2021
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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
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Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip Torr, Song Bai, and Xiaojuan Qi · 2022
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
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Label, verify, correct: A simple few shot object detection method
Prannay Kaul, Weidi Xie, and Andrew Zisserman · 2022
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The majority can help the minority: Context-rich minority oversampling for long-tailed classification
Seulki Park, Youngkyu Hong, Byeongho Heo, Sangdoo Yun, and Jin Young Choi · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Multi-faceted distillation of base-novel commonality for few-shot object detection
Shuang Wu, Wenjie Pei, Dianwen Mei, Fanglin Chen, Jiandong Tian, and Guangming Lu · 2022
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Kernelized few-shot object detection with efficient integral aggregation
Shan Zhang, Lei Wang, Naila Murray, and Piotr Koniusz · 2022
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An effective crop-paste pipeline for few-shot object detection
Shaobo Lin, Kun Wang, Xingyu Zeng, and Rui Zhao · 2023
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