D2
Computer Vision and Machine Learning

Apratim Bhattacharyya (PhD Student)

Personal Information

Education

  • 2016-present, Ph.D. candidate in Computer Science, Max Planck Institute for Informatics, Germany
  • 2014-2016, M.Sc.(Honors Degree) in Computer Science, Saarland University, Germany
  • 2010-2014, B.Tech. in Computer Engineering, National Institute of Technology, Karnataka, India

 

Links

Google Scholar | CV

Publications

2021

 

Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers,
A. Bhattacharyya, D. Reino, M. Fritz and B. Schiele,

Computer Vision and Pattern Recognition (CVPR), 2021.
Paper | arXivCode | Data | Video

 

2020

 

Normalizing Flows with Multi-scale Autoregressive Priors,
A. Bhattacharyya*, S. Mahajan*, M. Fritz, B. Schiele​​​​ and S. Roth,

Computer Vision and Pattern Recognition (CVPR), 2020 and INNF+@ICML'20.
Paper | Workshop (improved results) | Code | Video (*Equal contribution)

 

Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning, 
A. Salem, A. Bhattacharyya, M. Backes, M. Fritz and Y. Zhang, 

USENIX Security Symposium (USENIX Security), 2020.
arXiv

 

Haar Wavelet based Block Autoregressive Flows for Trajectories, 
A. Bhattacharyya, C. Straehle, M. Fritz and B. Schiele,

German Conference on Pattern Recognition, 2020 (oral) and ML4AD@NeurIPS’20.
arXivCode coming soon

 

SampleFix: Learning to Correct Programs by Sampling Diverse Fixes,
H. Hajipour, A. Bhattacharyya, M. Fritz,

CAP@NeurIPS’20.
arXiv

 

2019

 

Conditional Flow Variational Autoencoders for Structured Sequence Prediction,
A. Bhattacharyya, M. Hanselmann, M. Fritz, B. Schiele and C. Straehle,

Technical Report, 2019, BDL@NeurIPS’19 and ML4AD@NeurIPS’19 (oral).
arXiv | Video

 

"Best-of-Many-Samples" Distribution Matching,
A. Bhattacharyya, M. Fritz and B. Schiele,

Technical Report, 2019 and BDL@NeurIPS’19.
arXiv 

 

Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods,
A. Bhattacharyya, M. Fritz and B. Schiele, 

International Conference on Learning Representations (ICLR), 2019.
OpenReviewarXiv | Code+Data

 

2018

 

Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective,
A. Bhattacharyya, M. Fritz and B. Schiele,

Computer Vision and Pattern Recognition (CVPR), 2018 (oral).
Paper | arXiv | Code

 

Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty,
A. Bhattacharyya, M. Fritz and B. Schiele,  

Computer Vision and Pattern Recognition (CVPR), 2018.
Paper | arXiv | Code+Data

 

Long-Term Image Boundary Prediction,
A. Bhattacharyya, M. Malinowski, B. Schiele and M. Fritz, 

AAAI Conference on Artificial Intelligence, 2018.
Paper | arXiv

 

2017

 

Long-Term On-Board Prediction of Pedestrians in Traffic Scenes,
A. Bhattacharyya, M. Fritz and B. Schiele,

Conference on Robot Learning (CoRL), 2017, Workshop Track.
Paper

 

Efficiently Summarising Event Sequences with Rich Interleaving Patterns,
A. Bhattacharyya and J. Vreeken,

SIAM International Conference on Data Mining (SDM), 2017.
Paper | arXiv

 

2016

 

Long Term Boundary Extrapolation for Deterministic Motion,
A. Bhattacharyya, M. Malinowski and M. Fritz,

NIPS Workshop on Intuitive Physics, 2016.
Paper