CVPR

Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem

Matthias De Lange, Xu Jia, Sarah Parisot, Ales Leonardis, Gregory Slabaugh, Tinne Tuytelaars

Comments CVPR 2020

Journal ref Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2020

SSM-Net for Plants Disease Identification in Low Data Regime

Shruti Jadon

Comments 5 pages, 7 Figures

Journal ref Poster @CVPR workshop, Proceedings at IEEE / ITU International Conference on Artificial Intelligence for Good 2020

Image Compression with Encoder-Decoder Matched Semantic Segmentation

Trinh Man Hoang, Jinjia Zhou, Yibo Fan

Journal ref 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, 2020, pp. 619-623

ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning

Weiwei Sun, Wei Jiang, Eduard Trulls, Andrea Tagliasacchi, Kwang Moo Yi

Comments CVPR 2020

GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning

Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Hoi-Jun Yoo

Comments 10 pages, 10 figures, CVPR 2021 Submitted

Deep Parametric Continuous Convolutional Neural Networks

Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun

Comments Accepted by CVPR 2018

End-to-end Interpretable Neural Motion Planner

Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun

Comments CVPR 2019 (Oral)

Effect of Annotation Errors on Drone Detection with YOLOv3

Aybora Koksal, Kutalmis Gokalp Ince, A. Aydin Alatan

Comments Best Paper Award at The 1st Anti-UAV Workshop & Challenge - CVPR Workshops, 2020

OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression

Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun

Comments CVPR 2020 (Oral)

Distilling Knowledge from Graph Convolutional Networks

Yiding Yang, Jiayan Qiu, Mingli Song, Dacheng Tao, Xinchao Wang

Comments Accepted by CVPR 2020

Adapting JPEG XS gains and priorities to tasks and contents

Benoit Brummer, Christophe De Vleeschouwer

Comments CLIC at CVPR 2020

Journal ref Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, pp. 164-165

Towards Backward-Compatible Representation Learning

Yantao Shen, Yuanjun Xiong, Wei Xia, Stefano Soatto

Comments Accepted to CVPR 2020 as oral, revised version

Hierarchical Conditional Relation Networks for Multimodal Video Question Answering

Thao Minh Le, Vuong Le, Svetha Venkatesh, Truyen Tran

Comments Major extension of our CVPR'20 paper to handle long video with text. arXiv admin note: substantial text overlap with arXiv:2002.10698

Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search

Chaoyang He, Murali Annavaram, Salman Avestimehr

Comments accepted to CVPR 2020 workshop on neural architecture search and beyond for representation learning. Code is released at https://fedml.ai

Learning a Dynamic Map of Visual Appearance

Tawfiq Salem, Scott Workman, Nathan Jacobs

Comments IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020

Multi-Task Multi-Sensor Fusion for 3D Object Detection

Ming Liang, Bin Yang, Yun Chen, Rui Hu, Raquel Urtasun

Comments CVPR 2019

Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net

Wenjie Luo, Bin Yang, Raquel Urtasun

Comments CVPR 2018 Oral

Hierarchical Recurrent Attention Networks for Structured Online Maps

Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun

Comments Published at CVPR 2018

Self-supervised Learning of Interpretable Keypoints from Unlabelled Videos

Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi

Comments CVPR 2020 (oral). Project page: http://www.robots.ox.ac.uk/~vgg/research/unsupervised_pose/

Journal ref Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 8787-8797

Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation ($\text{POINT}^2$)

Haofu Liao, Wei-An Lin, Jiarui Zhang, Jingdan Zhang, Jiebo Luo, S. Kevin Zhou

Comments This work has been accepted to CVPR 2019

Convolutional Recurrent Network for Road Boundary Extraction

Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun

Journal ref CVPR 2019

Alleviating Noisy Data in Image Captioning with Cooperative Distillation

Pierre Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff

Comments CVPR 2020 VizWiz Challenge

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

Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan

Comments CVPR'20. More at https://www.cs.cmu.edu/~peiyunh/wysiwyg

Learning to Localize Through Compressed Binary Maps

Xinkai Wei, Ioan Andrei Bârsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun

Comments 18 pages, 12 figures, 6 tables; Presented at CVPR 2019

Journal ref Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 10316-10324

Dynamic Traffic Modeling From Overhead Imagery

Scott Workman, Nathan Jacobs

Comments IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020

M2m: Imbalanced Classification via Major-to-minor Translation

Jaehyung Kim, Jongheon Jeong, Jinwoo Shin

Comments 12 pages; CVPR 2020

Robust One Shot Audio to Video Generation

Neeraj Kumar, Srishti Goel, Ankur Narang, Mujtaba Hasan

Comments Accepted in CVPR Deep Vision 2020. arXiv admin note: text overlap with arXiv:2012.07304

Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration

Diana Mateus, Radu Horaud, David Knossow, Fabio Cuzzolin, Edmond Boyer

Journal ref IEEE Conference on Computer Vision and Pattern Recognition, 2008

Multivariate Confidence Calibration for Object Detection

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia, Anselm Haselhoff

Comments Accepted on CVPR 2020 Workshop: "2nd Workshop on Safe Artificial Intelligence for Automated Driving (SAIAD)"

Dependency Decomposition and a Reject Option for Explainable Models

Jan Kronenberger, Anselm Haselhoff

Comments Accepted at CVPR 2019 Workshop "DThree19: Dependable Deep Detectors"