2026
CVPR 2026 Findings
A2Z-10M+: Geometric Deep Learning with A-to-Z BRep Annotations for AI-Assisted CAD Modeling and Reverse Engineering
Pritham Kumar Jena, Bhavika Baburaj, Tushar Anand, Vedant Dutta, Vineeth Ulavala, Sk Aziz Ali
The largest compilation of 10 million multi-modal annotations and metadata for 1 million ABC CAD models, enabling unprecedented BRep learning with high-resolution meshes, 3D hand-drawn sketches, geometric and topological information, and textual captions.
2026
ICRA 2026
First Author
DenVisCoM: Dense Vision Correspondence Mamba for Efficient and Real-time Optical Flow and Stereo Estimation
Tushar Anand et al.
A novel Mamba block and hybrid architecture for joint, accurate, real-time estimation of optical flow and disparity. Addresses the three-way trade-off of inference speed, memory footprint, and accuracy in dense multi-view geometry tasks.
2026
ICRA 2026
First Author
DensePercept-NCSSD: Vision Mamba towards Real-time Dense Visual Perception with Non-Causal State Space Duality
Tushar Anand et al.
A non-causal Mamba block-based model for unified real-time optical flow and disparity estimation. Fuses pairwise input images within a non-causal selective state space, reducing inference times while maintaining high accuracy and low GPU memory footprint.
2025
ICASSP 2025
Equal Contribution
ViM-Disparity: Bridging the Gap of Speed, Accuracy and Memory for Disparity Map Generation
Maheswar Bora*, Tushar Anand*, Saurabh Atreya, Aritra Mukherjee, Abhijit Das
A Visual Mamba (ViM) based architecture that dissolves the speed–accuracy–memory trade-off for real-time disparity map generation, along with a novel joint performance measure for DMG evaluation.