no code implementations • 26 Mar 2024 • Astitva Srivastava, Pranav Manu, Amit Raj, Varun Jampani, Avinash Sharma
We achieve this by first learning a latent representation of 3D garments using a novel coarse-to-fine training strategy and a loss for latent disentanglement, promoting better latent interpolation.
no code implementations • 6 Jan 2024 • Shanthika Naik, Kunwar Singh, Astitva Srivastava, Dhawal Sirikonda, Amit Raj, Varun Jampani, Avinash Sharma
We propose a novel self-supervised framework for retargeting non-parameterized 3D garments onto 3D human avatars of arbitrary shapes and poses, enabling 3D virtual try-on (VTON).
no code implementations • 4 Dec 2023 • Chandradeep Pokhariya, Ishaan N Shah, Angela Xing, Zekun Li, Kefan Chen, Avinash Sharma, Srinath Sridhar
Since our representation uses Gaussian primitives, it enables us to efficiently and accurately estimate contacts between the hand and the object.
no code implementations • 20 Nov 2023 • Sushovan Chanda, Amogh Tiwari, Lokender Tiwari, Brojeshwar Bhowmick, Avinash Sharma, Hrishav Barua
Recovering temporally consistent 3D human body pose, shape and motion from a monocular video is a challenging task due to (self-)occlusions, poor lighting conditions, complex articulated body poses, depth ambiguity, and limited availability of annotated data.
1 code implementation • 23 Oct 2022 • Surabhi Gupta, Ashwath Shetty, Avinash Sharma
Virtual presence is a promising direction in communication and recreation for the future.
no code implementations • 27 Aug 2022 • Astitva Srivastava, Chandradeep Pokhariya, Sai Sagar Jinka, Avinash Sharma
Existing approaches for 3D garment reconstruction either assume a predefined template for the garment geometry (restricting them to fixed clothing styles) or yield vertex colored meshes (lacking high-frequency textural details).
no code implementations • 7 Aug 2022 • Arvind Subramaniam, Avinash Sharma
Following a preliminary pruning step, N2NSkip connections are randomly added between individual neurons/channels of the pruned network, while maintaining the overall sparsity of the network.
no code implementations • 24 May 2022 • Sai Sagar Jinka, Astitva Srivastava, Chandradeep Pokhariya, Avinash Sharma, P. J. Narayanan
The parametric body prior enforces geometrical consistency on the body shape and pose, while the non-parametric representation models loose clothing and handle self-occlusions as well.
1 code implementation • 7 Jan 2022 • Shanthika Naik, Aryamaan Jain, Avinash Sharma, KS Rajan
Our framework is an example-based method that attempts to overcome the limitations of existing methods by learning a latent space from a real-world terrain dataset.
no code implementations • 2 Dec 2021 • Surabhi Gupta, Ashwath Shetty, Avinash Sharma
Traditionally, video conferencing is a widely adopted solution for telecommunication, but a lack of immersiveness comes inherently due to the 2D nature of facial representation.
no code implementations • 30 Nov 2021 • Sahib Majithia, Sandeep N. Parameswaran, Sadbhavana Babar, Vikram Garg, Astitva Srivastava, Avinash Sharma
Subsequently, we use these landmarks to perform Thin-Plate-Spline-based texture transfer on UV map panels.
no code implementations • 21 Jun 2021 • Avinash Sharma, Radu Horaud, Diana Mateus
We discuss solutions for the exact and inexact graph isomorphism problems and recall the main spectral properties of the combinatorial graph Laplacian; We provide a novel analysis of the commute-time embedding that allows us to interpret the latter in terms of the PCA of a graph, and to select the appropriate dimension of the associated embedded metric space; We derive a unit hyper-sphere normalization for the commute-time embedding that allows us to register two shapes with different samplings; We propose a novel method to find the eigenvalue-eigenvector ordering and the eigenvector signs using the eigensignature (histogram) which is invariant to the isometric shape deformations and fits well in the spectral graph matching framework, and we present a probabilistic shape matching formulation using an expectation maximization point registration algorithm which alternates between aligning the eigenbases and finding a vertex-to-vertex assignment.
no code implementations • CVPR 2021 • Nicolas Robidoux, Luis E. Garcia Capel, Dong-eun Seo, Avinash Sharma, Federico Ariza, Felix Heide
Traditionally, hardware ISP settings used by downstream vision modules have been chosen by domain experts.
no code implementations • 9 Jun 2021 • Sai Sagar Jinka, Rohan Chacko, Astitva Srivastava, Avinash Sharma, P. J. Narayanan
3D human body reconstruction from monocular images is an interesting and ill-posed problem in computer vision with wider applications in multiple domains.
no code implementations • 19 Dec 2020 • Neeraj Battan, Yudhik Agrawal, Veeravalli Saisooryarao, Aman Goel, Avinash Sharma
Synthesis of long-term human motion skeleton sequences is essential to aid human-centric video generation with potential applications in Augmented Reality, 3D character animations, pedestrian trajectory prediction, etc.
1 code implementation • 4 Oct 2020 • Ashish Kubade, Diptiben Patel, Avinash Sharma, K. S. Rajan
Terrain, representing features of an earth surface, plays a crucial role in many applications such as simulations, route planning, analysis of surface dynamics, computer graphics-based games, entertainment, films, to name a few.
no code implementations • 3 Jul 2020 • Ashish Kubade, Avinash Sharma, K S Rajan
High resolution Digital Elevation Models(DEMs) are an important requirement for many applications like modelling water flow, landslides, avalanches etc.
no code implementations • 27 Feb 2020 • Hiteshi Jain, Gaurav Harit, Avinash Sharma
the reference video and map those variations to the final score.
1 code implementation • 16 Feb 2020 • Sai Sagar Jinka, Rohan Chacko, Avinash Sharma, P. J. Narayanan
We introduce PeeledHuman - a novel shape representation of the human body that is robust to self-occlusions.
2 code implementations • 19 Aug 2019 • Abbhinav Venkat, Chaitanya Patel, Yudhik Agrawal, Avinash Sharma
3D Human Body Reconstruction from a monocular image is an important problem in computer vision with applications in virtual and augmented reality platforms, animation industry, en-commerce domain, etc.
no code implementations • 15 Aug 2019 • Neeraj Battan, Abbhinav Venkat, Avinash Sharma
3D Human Motion Indexing and Retrieval is an interesting problem due to the rise of several data-driven applications aimed at analyzing and/or re-utilizing 3D human skeletal data, such as data-driven animation, analysis of sports bio-mechanics, human surveillance etc.
no code implementations • 18 Sep 2018 • Abbhinav Venkat, Sai Sagar Jinka, Avinash Sharma
In this paper, we propose a deep learning based solution for textured 3D reconstruction of human body shapes from a single view RGB image.