Akash Sengupta

According to our database, Akash Sengupta authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans.

Akash Sengupta, Thiemo Alldieck, Nikos Kolotouros, Enric Corona, Andrei Zanfir, Cristian Sminchisescu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Radical Sylvester-Gallai Theorem for Tuples of Quadratics.

Abhibhav Garg, Rafael Mendes de Oliveira, Shir Peleg, Akash Sengupta

Electron. Colloquium Comput. Complex., 2023

HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation.

Akash Sengupta, Ignas Budvytis, Roberto Cipolla

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Radical Sylvester-Gallai for Cubics.

Rafael Mendes de Oliveira, Akash Sengupta

Electron. Colloquium Comput. Complex., 2022

Robust Radical Sylvester-Gallai Theorem for Quadratics.

Abhibhav Garg, Rafael Mendes de Oliveira, Akash Sengupta

Electron. Colloquium Comput. Complex., 2022

2021

Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild.

Akash Sengupta, Ignas Budvytis, Roberto Cipolla

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Probabilistic 3D Human Shape and Pose Estimation From Multiple Unconstrained Images in the Wild.

Akash Sengupta, Ignas Budvytis, Roberto Cipolla

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Probabilistic Estimation of 3D Human Shape and Pose with a Semantic Local Parametric Model.

Akash Sengupta, Ignas Budvytis, Roberto Cipolla

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wild.

Akash Sengupta, Roberto Cipolla, Ignas Budvytis

Proceedings of the 31st British Machine Vision Conference 2020, 2020