Fetching the paper…
Reading the bibliography…
We seek to detect visual relations in images of the form of triplets t = (subject, predicate, object), such as "person riding dog", where training examples of the individual entities are available but their combinations are unseen at training.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
Tabula rasa: Model transfer for object category detection
Yusuf Aytar and Andrew Zisserman · 2011
Earlier work this paper cites.
Recognition using visual phrases
Mohammad Amin Sadeghi and Ali Farhadi · 2011
Earlier work this paper cites.
A latent factor model for highly multi-relational data
Rodolphe Jenatton, Nicolas L Roux, Antoine Bordes, and Guillaume R Obozinski · 2012
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Earlier work this paper cites.
Learning everything about anything: Webly-supervised visual concept learning
Santosh Kumar Divvala, Ali Farhadi, and Carlos Guestrin · 2014
Earlier work this paper cites.
Deep fragment embeddings for bidirectional image sentence mapping
Andrej Karpathy, Armand Joulin, and Li Fei-Fei · 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.
Hico: A benchmark for recognizing human-object interactions in images
Yu-Wei Chao, Zhan Wang, Yugeng He, Jiaxuan Wang, and Jia Deng · 2015
Earlier work this paper cites.
Saurabh Gupta and Jitendra Malik · 2015
Earlier work this paper cites.
Segment-phrase table for semantic segmentation, visual entailment and paraphrasing
Hamid Izadinia, Fereshteh Sadeghi, Santosh Kumar Divvala, Yejin Choi, and Ali Farhadi · 2015
Earlier work this paper cites.
Image retrieval using scene graphs
Justin Johnson, Ranjay Krishna, Michael Stark, Li-Jia Li, David A Shamma, Michael S Bernstein, and Li Fei-Fei · 2015
Earlier work this paper cites.
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
Bryan A. Plummer, Liwei Wang, Chris M. Cervantes, Juan C. Caicedo, Julia Hockenmaier, and Svetlana Lazebnik · 2015
Earlier work this paper cites.
Learning semantic relationships for better action retrieval in images
Vignesh Ramanathan, Congcong Li, Jia Deng, Wei Han, Zhen Li, Kunlong Gu, Yang Song, Samy Bengio, Chuck Rossenberg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Deep visual analogy-making
Scott E. Reed, Yi Zhang, Yuting Zhang, and Honglak Lee · 2015
Cited alongside, same era.
Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Cited alongside, same era.
Describing common human visual actions in images
Matteo Ruggero Ronchi and Pietro Perona · 2015
Cited alongside, same era.
Viske: Visual knowledge extraction and question answering by visual verification of relation phrases
Fereshteh Sadeghi, Santosh K Divvala, and Ali Farhadi · 2015
Cited alongside, same era.
Visalogy: Answering visual analogy questions
Fereshteh Sadeghi, C. Lawrence Zitnick, and Ali Farhadi · 2015
Cited alongside, same era.
Learning to generalize to new compositions in image understanding
From red wine to red tomato: Composition with context
Ishan Misra, Abhinav Gupta, and Martial Hebert · 2017
Later among the works it cites.
Weakly-supervised learning of visual relations
Julia Peyre, Ivan Laptev, Cordelia Schmid, and Josef Sivic · 2017
Later among the works it cites.
Phrase localization and visual relationship detection with comprehensive linguistic cues
Bryan A. Plummer, Arun Mallya, Christopher M. Cervantes, Julia Hockenmaier, and Svetlana Lazebnik · 2017
Later among the works it cites.
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G.T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap · 2017
Later among the works it cites.
Visual relationship detection with internal and external linguistic knowledge distillation
Ruichi Yu, Ang Li, Vlad I. Morariu, and Larry S. Davis · 2017
Later among the works it cites.
Visual translation embedding network for visual relation detection
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yuval Atzmon, Jonathan Berant, Vahid Kezami, Amir Globerson, and Gal Chechik · 2016
Cited alongside, same era.
Interaction networks for learning about objects, relations and physics
Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimeneze Rezende, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Densecap: Fully convolutional localization networks for dense captioning
Justin Johnson, Andrej Karpathy, and Li Fei-Fei · 2016
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2016
Cited alongside, same era.
Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, Michael Bernstein, and Li Fei-Fei · 2016
Cited alongside, same era.
Visual relationship detection with language priors
Cewu Lu, Ranjay Krishna, Michael Bernstein, and Li Fei-Fei · 2016
Cited alongside, same era.
Learning deep structure-preserving image-text embeddings
Liwei Wang, Yin Li, and Svetlana Lazebnik · 2016
Cited alongside, same era.
Hanwang Zhang, Zawlin Kyaw, Shih-Fu Chang, and Tat-Seng Chua · 2017
Later among the works it cites.
Towards context-aware interaction recognition for visual relationship detection
Bohan Zhuang, Lingqiao Liu, Chunhua Shen, and Ian Reid · 2017
Later among the works it cites.
Learning to detect human-object interactions
Yu-Wei Chao, Yunfan Liu, Xieyang Liu, Huayi Zeng, and Jia Deng · 2018
Closest in time.
Ican: Instance-centric attention network for human-object interaction detection
Chen Gao, Yuliang Zou, and Jia-Bin Huang · 2018
Closest in time.
Detectron
Ross Girshick, Ilija Radosavovic, Georgia Gkioxari, Piotr Dollár, and Kaiming He · 2018
Closest in time.
Detecting and recognizing human-object interactions
Georgia Gkioxari, Ross Girshick, and Kaiming He · 2018
Closest in time.
Tensorize, factorize and regularize: Robust visual relationship learning
Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, and Vikas Singh · 2018
Closest in time.
Compositional learning for human object interaction
Keizo Kato, Yi Li, and Abhinav Gupta · 2018
Closest in time.
Learning human-object interactions by graph parsing neural networks
Siyuan Qi, Wenguan Wang, Baoxiong Jia, Jianbing Shen, and Song-Chun Zhu · 2018
Closest in time.
Scaling human-object interaction recognition through zero-shot learning
Liyue Shen, Serena Yeung, Judy Hoffman, Greg Mori, and Li Fei-Fei · 2018
Closest in time.
Large-scale visual relationship understanding
Ji Zhang, Yannis Kalantidis, Marcus Rohrbach, Manohar Paluri, Ahmed Elgammal, and Mohamed Elhoseiny · 2019
Closest in time.