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Background Splitting: Finding Rare Classes in a Sea of Background

Aug 28, 2020
Ravi Teja Mullapudi, Fait Poms, William R. Mark, Deva Ramanan, Kayvon Fatahalian


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What-If Motion Prediction for Autonomous Driving

Aug 24, 2020
Siddhesh Khandelwal, William Qi, Jagjeet Singh, Andrew Hartnett, Deva Ramanan

* 16 pages, 6 tables, 6 figures 

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Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild

Aug 19, 2020
Jason Y. Zhang, Sam Pepose, Hanbyul Joo, Deva Ramanan, Jitendra Malik, Angjoo Kanazawa

* In ECCV 2020. v2: Updated Related Work 

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4D Visualization of Dynamic Events from Unconstrained Multi-View Videos

May 27, 2020
Aayush Bansal, Minh Vo, Yaser Sheikh, Deva Ramanan, Srinivasa Narasimhan

* Project Page - http://www.cs.cmu.edu/~aayushb/Open4D/ 

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Towards Streaming Image Understanding

May 21, 2020
Mengtian Li, Yu-Xiong Wang, Deva Ramanan

* Project page is at https://www.cs.cmu.edu/~mengtial/proj/streaming/ 

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TAO: A Large-Scale Benchmark for Tracking Any Object

May 20, 2020
Achal Dave, Tarasha Khurana, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan

* Project page: http://taodataset.org/ 

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Learning Generative Models of Tissue Organization with Supervised GANs

Mar 31, 2020
Ligong Han, Robert F. Murphy, Deva Ramanan

* Accepted at WACV-18 

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Learning to Move with Affordance Maps

Feb 14, 2020
William Qi, Ravi Teja Mullapudi, Saurabh Gupta, Deva Ramanan

* Published at ICLR 2020. For code, see https://github.com/wqi/A2L 

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Unsupervised Any-to-Many Audiovisual Synthesis via Exemplar Autoencoders

Jan 13, 2020
Kangle Deng, Aayush Bansal, Deva Ramanan

* (1) Project summary is available at: https://www.youtube.com/watch?v=7BO0-Q3TLfI ; (2) Code is available at https://github.com/dunbar12138/Audiovisual-Synthesis ; and (3) A beta web-demo is available at: https://scs00197.sp.cs.cmu.edu/ 

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Hierarchical Deep Stereo Matching on High-resolution Images

Dec 13, 2019
Gengshan Yang, Joshua Manela, Michael Happold, Deva Ramanan

* CVPR 2019 

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Inferring Distributions Over Depth from a Single Image

Dec 12, 2019
Gengshan Yang, Peiyun Hu, Deva Ramanan

* IROS 2019 

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What You See is What You Get: Exploiting Visibility for 3D Object Detection

Dec 10, 2019
Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan


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Learning to Optimally Segment Point Clouds

Dec 10, 2019
Peiyun Hu, David Held, Deva Ramanan


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Are we asking the right questions in MovieQA?

Nov 08, 2019
Bhavan Jasani, Rohit Girdhar, Deva Ramanan

* Spotlight presentation at CLVL workshop, ICCV 2019. Project page: https://bhavanj.github.io/MovieQAWithoutMovies/ 

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Argoverse: 3D Tracking and Forecasting with Rich Maps

Nov 06, 2019
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, James Hays

* CVPR 2019 

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Learning to Track Any Object

Oct 25, 2019
Achal Dave, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan

* To be presented at the Holistic Video Understanding workshop at ICCV 

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CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning

Oct 10, 2019
Rohit Girdhar, Deva Ramanan

* Webpage: https://rohitgirdhar.github.io/CATER 

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MetaPix: Few-Shot Video Retargeting

Oct 10, 2019
Jessica Lee, Deva Ramanan, Rohit Girdhar

* Short version accepted to NeurIPS'19 MetaLearn Workshop. Webpage: https://imjal.github.io/MetaPix/ 

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Weakly-supervised Action Localization with Background Modeling

Aug 19, 2019
Phuc Xuan Nguyen, Deva Ramanan, Charless C. Fowlkes

* To appear at ICCV 2019 

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Growing a Brain: Fine-Tuning by Increasing Model Capacity

Jul 18, 2019
Yu-Xiong Wang, Deva Ramanan, Martial Hebert

* CVPR 

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Shapes and Context: In-the-Wild Image Synthesis & Manipulation

Jun 11, 2019
Aayush Bansal, Yaser Sheikh, Deva Ramanan

* CVPR 2019 
* Project Page: http://www.cs.cmu.edu/~aayushb/OpenShapes/ 

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A systematic framework for natural perturbations from videos

Jun 05, 2019
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt

* 16 pages, 5 tables, 6 figures. Paper Website: https://modestyachts.github.io/natural-perturbations-website/ 

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Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints

May 12, 2019
Mengtian Li, Ersin Yumer, Deva Ramanan


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Towards Segmenting Everything That Moves

Feb 11, 2019
Achal Dave, Pavel Tokmakov, Deva Ramanan


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DistInit: Learning Video Representations without a Single Labeled Video

Jan 26, 2019
Rohit Girdhar, Du Tran, Lorenzo Torresani, Deva Ramanan


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Photo-Sketching: Inferring Contour Drawings from Images

Jan 02, 2019
Mengtian Li, Zhe Lin, Radomir Mech, Ersin Yumer, Deva Ramanan

* WACV 2019. For code and dataset, see http://www.cs.cmu.edu/~mengtial/proj/sketch/ 

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Online Model Distillation for Efficient Video Inference

Dec 06, 2018
Ravi Teja Mullapudi, Steven Chen, Keyi Zhang, Deva Ramanan, Kayvon Fatahalian


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Cross-Domain Image Matching with Deep Feature Maps

Oct 01, 2018
Bailey Kong, James Supancic, Deva Ramanan, Charless C. Fowlkes


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