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Computer Science

D-Index
58
Citations
13884
World Ranking
3620
National Ranking
1737

Overview

Manmohan Chandraker is affiliated with the University of California, San Diego in the United States. Their research primarily spans the areas of computer science and engineering, with a significant focus on computer vision and pattern recognition, artificial intelligence, and computer graphics and computer-aided design.

Their recent published papers include the following:

  • Modulated Periodic Activations for Generalizable Local Functional Representations, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation, 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Learning Cross-Modal Contrastive Features for Video Domain Adaptation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Adversarial Learning of Privacy-Preserving and Task-Oriented Representations, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Real-Time Radiance Fields for Single-Image Portrait View Synthesis, 2023, ACM Transactions on Graphics

The scientist collaborates frequently with a number of coauthors, including:

  • Samuel Schulter (21 collaborations)
  • Tarun Kalluri (14 collaborations)
  • Ravi Ramamoorthi (13 collaborations)
  • Yumin Suh (13 collaborations)
  • Yi-Hsuan Tsai (12 collaborations)

Manmohan Chandraker has been published regularly in several venues. The most frequent publication venues are:

  • arXiv (Cornell University), 67 publications
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 6 publications
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 3 publications
  • Lecture Notes in Computer Science, 3 publications
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2 publications

Their research covers a wide range of topics, including:

  • Advanced Vision and Imaging
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Computer Graphics and Visualization Techniques
  • Robotics and Sensor-Based Localization
  • Advanced Image and Video Retrieval Techniques

These topics correspond closely with their main and subfields of study, which include:

  • Computer Science
  • Engineering
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Computational Mechanics
  • Aerospace Engineering

Best Publications

  • Learning to Adapt Structured Output Space for Semantic Segmentation

    Yi-Hsuan Tsai;Wei-Chih Hung;Samuel Schulter;Kihyuk Sohn

  • DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents

    Namhoon Lee;Wongun Choi;Paul Vernaza;Christopher B. Choy

  • Person Re-identification in the Wild

    Liang Zheng;Hengheng Zhang;Shaoyan Sun;Manmohan Chandraker

  • Learning efficient object detection models with knowledge distillation

    Guobin Chen;Wongun Choi;Xiang Yu;Tony Han

  • Learning Random-Walk Label Propagation for Weakly-Supervised Semantic Segmentation

    Paul Vernaza;Manmohan Chandraker

  • Towards Large-Pose Face Frontalization in the Wild

    Xi Yin;Xiang Yu;Kihyuk Sohn;Xiaoming Liu

  • Domain Adaptation for Structured Output via Discriminative Patch Representations

    Yi-Hsuan Tsai;Kihyuk Sohn;Samuel Schulter;Manmohan Chandraker

  • Feature Transfer Learning for Face Recognition With Under-Represented Data

    Xi Yin;Xiang Yu;Kihyuk Sohn;Xiaoming Liu

  • IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments

    Girish Varma;Anbumani Subramanian;Anoop Namboodiri;Manmohan Chandraker

  • Learning to reconstruct shape and spatially-varying reflectance from a single image

    Zhengqin Li;Zexiang Xu;Ravi Ramamoorthi;Kalyan Sunkavalli

  • Universal correspondence network

    Manmohan Chandraker;Silvio Savarese;Christopher Bongsoo Choy

  • Universal Correspondence Network

    Christopher B. Choy;JunYoung Gwak;Silvio Savarese;Manmohan Chandraker

  • Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image

    Zhengqin Li;Mohammad Shafiei;Ravi Ramamoorthi;Kalyan Sunkavalli

  • Deep Network Flow for Multi-object Tracking

    Samuel Schulter;Paul Vernaza;Wongun Choi;Manmohan Chandraker

  • A 4D Light-Field Dataset and CNN Architectures for Material Recognition

    Ting-Chun Wang;Jun-Yan Zhu;Ebi Hiroaki;Manmohan Chandraker

  • WarpNet: Weakly Supervised Matching for Single-View Reconstruction

    Angjoo Kanazawa;David W. Jacobs;Manmohan Chandraker

  • Robust Scale Estimation in Real-Time Monocular SFM for Autonomous Driving

    Shiyu Song;Manmohan Chandraker

  • Reconstruction-Based Disentanglement for Pose-Invariant Face Recognition

    Xi Peng;Xiang Yu;Kihyuk Sohn;Dimitris N. Metaxas

  • Materials for Masses: SVBRDF Acquisition with a Single Mobile Phone Image

    Zhengqin Li;Kalyan Sunkavalli;Manmohan Chandraker

  • Towards Universal Representation Learning for Deep Face Recognition

    Yichun Shi;Xiang Yu;Kihyuk Sohn;Manmohan Chandraker

  • ShadowCuts: Photometric Stereo with Shadows

    M. Chandraker;S. Agarwal;D. Kriegman

  • Practical Global Optimization for Multiview Geometry

    Fredrik Kahl;Sameer Agarwal;Manmohan Krishna Chandraker;David Kriegman

Frequent Co-Authors

Kihyuk Sohn
Kihyuk Sohn Google (United States)
Ravi Ramamoorthi
Ravi Ramamoorthi University of California, San Diego
David J. Kriegman
David J. Kriegman University of California, San Diego
Xiaoming Liu
Xiaoming Liu University of North Carolina at Chapel Hill
Kalyan Sunkavalli
Kalyan Sunkavalli Adobe Systems (United States)
Silvio Savarese
Silvio Savarese Stanford University
Ming-Hsuan Yang
Ming-Hsuan Yang University of California, Merced
Gregory D. Hager
Gregory D. Hager Johns Hopkins University
Sameer Agarwal
Sameer Agarwal Google (United States)
C. V. Jawahar
C. V. Jawahar International Institute of Information Technology, Hyderabad

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