I am an assistant professor in visual computing and a researcher primarily focused in the field of 3D computer vision, Visual AI and Automation.
Presently, I work in the Visual Computing and Computational Media Section at Texas A & M University, College Station Texas.
As a researcher, I am fascinated by how mathematical construction can precisely represent the perceptual concepts of images, such as 3D scene geometry, motions, lights, material, and color. I aim to
use these mathematical concepts to enable machines for a broader adoption using visual data.
Research Interests
Computer Vision, Visual AI, Spatial AI and Robotics. From time to time, I also investigate topics such as graph theory, topological manifolds, compressed sensing, and mathematical optimization.
Recent News
Recent Awards and Achievements
Current Students (Masters and Doctorate)
[Topic]: Human-Robot Interaction.
External Students or Informal Collaboration
Selected Recent Publications
ICGNet: A Unified Approach for Instance-Centric Grasping
Authors : René Zurbrügg, Yifan Liu, Francis Engelmann, Suryansh Kumar, Marco Hutter and othersInternational Conference on Robotics and Automation (ICRA), IEEE, 2024, Yokohama, Japan
Project Website Topic: Grasping, 3D Acquisition, Robotics.
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images
Authors : Nishant Jain, Suryansh Kumar*, Luc Van Gool.International Journal of Computer Vision (IJCV), Springer, 2024, IF: 19.5
Project Website Topic: View Synthesis, NeRF, Image-based Rendering.
Single Image Depth Prediction Made Better: A Multivariate Gaussian Take
Authors: Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Luc Van Gool.Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2023, Vancouver, Canada.
Project Website Topic: 3D Computer Vision, Deep Learning.
Enhanced Stable View-Synthesis
Authors: Nishant Jain*, Suryansh Kumar*, Luc Van Gool.Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2023, Vancouver, Canada.
Project Website Topic: 3D Computer Vision, Deep Learning, Neural Rendering.
Quantum Annealing for Single Image Super-Resolution
Authors: Han Yao Choong, Suryansh Kumar, Luc Van Gool. (Oral Presentation)8th New Trends in Image Restoration and Enhancement Workshop and Challenges (NTIRE).
Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2023, Vancouver, Canada.
Project Website Topic: Quantum Computing, Image Enhancement.
How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers
Authors: Junting Chen*, Guohao Li*, Suryansh Kumar, and othersRobotics Science and Systems (RSS), RSS Foundation, 2023, Daegu, South Korea.
Project Website Topic: Embodied-AI, Active SLAM, Navigation, Vision and Language.
VA-DepthNet: A Variational Approach to Single Image Depth Prediction
Authors: Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Luc Van Gool. (Spotlight Oral Presentation)International Conference on Learning Representations (ICLR), 2023, Kigali, Rwanda.
Project Website Topic: 3D Computer Vision, Deep Learning.
Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields
Authors: Soomin Lee, Le Chen, Jiahao Wang, and othersInternational Conference on Robotics and Automation (ICRA), IEEE, 2023, London, UK. (Oral Presentation)
Project Website Topic: 3D Computer Vision, Robotics, Information Theory.
Organic Priors in Non-Rigid Structure from Motion
Authors: Suryansh Kumar, Luc Van Gool. (Oral Presentation, Top 2.7% of the papers)European Conference on Computer Vision (ECCV), 2022, Tel-Aviv, Israel.
Project Website Topic: 3D Computer Vision, Algebra, Geometry, Compressed Sensing.