Fetching the paper…
Reading the bibliography…
Despite the importance of unsupervised object detection, to the best of our knowledge, there is no previous work addressing this problem.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
The essential guide to video processing
Alan C Bovik · 2009
Earlier work this paper cites.
ImageNet: A Large-Scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
Constrained parametric min-cuts for automatic object segmentation
Joao Carreira and Cristian Sminchisescu · 2010
Earlier work this paper cites.
Category independent object proposals
Ian Endres and Derek Hoiem · 2010
Earlier work this paper cites.
On the segmentation of 3d lidar point clouds
Bertrand Douillard, James Underwood, Noah Kuntz, Vsevolod Vlaskine, Alastair Quadros, Peter Morton, and Alon Frenkel · 2011
Earlier work this paper cites.
Bahman Bahmani, Benjamin Moseley, Andrea Vattani, Ravi Kumar, and Sergei Vassilvitskii · 2012
Earlier work this paper cites.
Motion segmentation of multiple objects from a freely moving monocular camera
Rahul Kumar Namdev, Abhijit Kundu, K Madhava Krishna, and CV Jawahar · 2012
Earlier work this paper cites.
Video object proposals
Gilad Sharir and Tinne Tuytelaars · 2012
Earlier work this paper cites.
Exploiting domain knowledge for object discovery
Alvaro Collet, Bo Xiong, Corina Gurau, Martial Hebert, and Siddhartha S Srinivasa · 2013
Earlier work this paper cites.
Object discovery in 3d scenes via shape analysis
Andrej Karpathy, Stephen Miller, and Li Fei-Fei · 2013
Earlier work this paper cites.
Fast Object Segmentation in Unconstrained Video
Anestis Papazoglou and Vittorio Ferrari · 2013
Earlier work this paper cites.
Image segmentation by cascaded region agglomeration
Zhile Ren and Gregory Shakhnarovich · 2013
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.
Online video seeds for temporal window objectness
Michael Van den Bergh, Gemma Roig, Xavier Boix, Santiago Manen, and Luc Van Gool · 2013
Earlier work this paper cites.
Multiscale combinatorial grouping
Pablo Arbeláez, Jordi Pont-Tuset, Jonathan T Barron, Ferran Marques, and Jitendra Malik · 2014
Earlier work this paper cites.
Lsda: Large scale detection through adaptation
Judy Hoffman, Sergio Guadarrama, Eric S Tzeng, Ronghang Hu, Jeff Donahue, Ross Girshick, Trevor Darrell, and Kate Saenko · 2014
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.
Spatio-temporal object detection proposals
Dan Oneata, Jérôme Revaud, Jakob Verbeek, and Cordelia Schmid · 2014
Earlier work this paper cites.
Discriminative unsupervised feature learning with exemplar convolutional neural networks
Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
Learning to segment moving objects in videos
Katerina Fragkiadaki, Pablo Arbelaez, Panna Felsen, and Jitendra Malik · 2015
Earlier work this paper cites.
Fast R-CNN
Ross Girshick · 2015
Earlier work this paper cites.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy · 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.
Weakly Supervised Deep Detection Networks
Hakan Bilen and Andrea Vedaldi · 2016
Earlier work this paper cites.
Fast range image-based segmentation of sparse 3d laser scans for online operation
Igor Bogoslavskyi and Cyrill Stachniss · 2016
Earlier work this paper cites.
Weakly supervised object localization with multi-fold multiple instance learning
Ramazan Gokberk Cinbis, Jakob Verbeek, and Cordelia Schmid · 2016
Earlier work this paper cites.
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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.
ContextLocNet: Context-aware Deep Network Models for Weakly Supervised Localization
Vadim Kantorov, Maxime Oquab, Minsu Cho, and Ivan Laptev · 2016
Earlier work this paper cites.
Vehicle detection from 3d lidar using fully convolutional network
Bo Li, Tianlei Zhang, and Tian Xia · 2016
Earlier work this paper cites.
Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation
Jordi Pont-Tuset, Pablo Arbelaez, Jonathan T Barron, Ferran Marques, and Jitendra Malik · 2016
Earlier work this paper cites.
Dense monocular depth estimation in complex dynamic scenes
Rene Ranftl, Vibhav Vineet, Qifeng Chen, and Vladlen Koltun · 2016
Earlier work this paper cites.
Large scale semi-supervised object detection using visual and semantic knowledge transfer
Yuxing Tang, Josiah Wang, Boyang Gao, Emmanuel Dellandréa, Robert Gaizauskas, and Liming Chen · 2016
Earlier work this paper cites.
Track and segment: An iterative unsupervised approach for video object proposals
Fanyi Xiao and Yong Jae Lee · 2016
Cited alongside, same era.
Unsupervised deep embedding for clustering analysis
Junyuan Xie, Ross Girshick, and Ali Farhadi · 2016
Cited alongside, same era.
Joint unsupervised learning of deep representations and image clusters
Jianwei Yang, Devi Parikh, and Dhruv Batra · 2016
Cited alongside, same era.
Efficient Online Segmentation for Sparse 3D Laser Scans
Igor Bogoslavskyi and Cyrill Stachniss · 2017
Cited alongside, same era.
Deep adaptive image clustering
Jianlong Chang, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, and Chunhong Pan · 2017
Cited alongside, same era.
Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
Cited alongside, same era.
Scaling and benchmarking self-supervised visual representation learning
Priya Goyal, Dhruv Mahajan, Abhinav Gupta, and Ishan Misra · 2019
Later among the works it cites.
Lvis: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
Later among the works it cites.
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2019
Later among the works it cites.
Unsupervised deep learning by neighbourhood discovery
Jiabo Huang, Qi Dong, Shaogang Gong, and Xiatian Zhu · 2019
Later among the works it cites.
Consistency-based semi-supervised learning for object detection
Jisoo Jeong, Seungeui Lee, Jeesoo Kim, and Nojun Kwak · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Weakly Supervised Cascaded Convolutional Networks
Ali Diba, Vivek Sharma, Ali Pazandeh, Hamed Pirsiavash, and Luc Van Gool · 2017
Cited alongside, same era.
Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks
Martin Engelcke, Dushyant Rao, Dominic Zeng Wang, Chi Hay Tong, and Ingmar Posner · 2017
Cited alongside, same era.
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Cited alongside, same era.
3d fully convolutional network for vehicle detection in point cloud
Bo Li · 2017
Cited alongside, same era.
Feature Pyramid Networks for Object Detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Cited alongside, same era.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Cited alongside, same era.
Invariant information clustering for unsupervised image classification and segmentation
Xu Ji, João F Henriques, and Andrea Vedaldi · 2019
Later among the works it cites.
Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Later among the works it cites.
Multi-task multi-sensor fusion for 3d object detection
Ming Liang, Bin Yang, Yun Chen, Rui Hu, and Raquel Urtasun · 2019
Later among the works it cites.
Competitive collaboration: Joint unsupervised learning of depth, camera motion, optical flow and motion segmentation
Anurag Ranjan, Varun Jampani, Lukas Balles, Kihwan Kim, Deqing Sun, Jonas Wulff, and Michael J Black · 2019
Later among the works it cites.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
Later among the works it cites.
Roarnet: A robust 3d object detection based on region approximation refinement
Kiwoo Shin, Youngwook Paul Kwon, and Masayoshi Tomizuka · 2019
Later among the works it cites.
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2019
Later among the works it cites.
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
Later among the works it cites.
Zhixin Wang and Kui Jia · 2019
Later among the works it cites.
Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
Later among the works it cites.
Missing labels in object detection
Mengmeng Xu, Yancheng Bai, Bernard Ghanem, Boxiao Liu, Yan Gao, Nan Guo, Xiaochun Ye, Fang Wan, Haihang You, Dongrui Fan, et al · 2019
Later among the works it cites.
Unsupervised moving object detection via contextual information separation
Yanchao Yang, Antonio Loquercio, Davide Scaramuzza, and Stefano Soatto · 2019
Later among the works it cites.
Std: Sparse-to-dense 3d object detector for point cloud
Zetong Yang, Yanan Sun, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2019
Later among the works it cites.
Local aggregation for unsupervised learning of visual embeddings
Chengxu Zhuang, Alex Lin Zhai, and Daniel Yamins · 2019
Later among the works it cites.
Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
Closest in time.
A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Closest in time.
Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey E Hinton · 2020
Closest in time.
Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
Closest in time.
Learning representations by predicting bags of visual words
Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord · 2020
Closest in time.
Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
Closest in time.
Deep learning for 3d point clouds: A survey
Yulan Guo, Hanyun Wang, Qingyong Hu, Hao Liu, Li Liu, and Mohammed Bennamoun · 2020
Closest in time.
Fast lidar clustering by density and connectivity
Frederik Hasecke, Lukas Hahn, and Anton Kummert · 2020
Closest in time.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Closest in time.
Self-supervised learning: Generative or contrastive
Xiao Liu, Fanjin Zhang, Zhenyu Hou, Zhaoyu Wang, Li Mian, Jing Zhang, and Jie Tang · 2020
Closest in time.
Equalization loss for long-tailed object recognition
Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, and Junjie Yan · 2020
Closest in time.
Proposal learning for semi-supervised object detection
Peng Tang, Chetan Ramaiah, Ran Xu, and Caiming Xiong · 2020
Closest in time.
Scan: Learning to classify images without labels
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Marc Proesmans, and Luc Van Gool · 2020
Closest in time.
3dssd: Point-based 3d single stage object detector
Zetong Yang, Yanan Sun, Shu Liu, and Jiaya Jia · 2020
Closest in time.
Semi-supervised object detection with sparsely annotated dataset
Jihun Yoon, Seungbum Hong, Sanha Jeong, and Min-Kook Choi · 2020
Closest in time.
Solving missing-annotation object detection with background recalibration loss
Han Zhang, Fangyi Chen, Zhiqiang Shen, Qiqi Hao, Chenchen Zhu, and Marios Savvides · 2020
Closest in time.