2 citations · 8 across the 15 of their papers we have counts for
17 papers
Imaging Hidden Objects with Consumer LiDAR via Motion Induced Sampling
Siddharth Somasundaram, Aaron Young, Akshat Dave +2
LiDARs are being increasingly deployed for consumer imaging in handheld, wearable, and robotic applications. These sensors can capture the time-of-flight of light at picosecond res…
Shoot-Bounce-3D: Single-Shot Occlusion-Aware 3D from Lidar by Decomposing Two-Bounce Light
Tzofi Klinghoffer, Siddharth Somasundaram, Xiaoyu Xiang +5
3D scene reconstruction from a single measurement is challenging, especially in the presence of occluded regions and specular materials, such as mirrors. We address these challenge…
Task-Driven Implicit Representations for Automated Design of LiDAR Systems
Nikhil Behari, Aaron Young, Tzofi Klinghoffer +2
Imaging system design is a complex, time-consuming, and largely manual process; LiDAR design, ubiquitous in mobile devices, autonomous vehicles, and aerial imaging platforms, adds…
What if Eye...? Computationally Recreating Vision Evolution
Kushagra Tiwary, Aaron Young, Zaid Tasneem +6
Vision systems in nature show remarkable diversity, from simple light-sensitive patches to complex camera eyes with lenses. While natural selection has produced these eyes through…
Blurred LiDAR for Sharper 3D: Robust Handheld 3D Scanning with Diffuse LiDAR and RGB
Nikhil Behari, Aaron Young, Siddharth Somasundaram +3
3D surface reconstruction is essential across applications of virtual reality, robotics, and mobile scanning. However, RGB-based reconstruction often fails in low-texture, low-ligh…
Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDAR
Aaron Young, Nevindu M. Batagoda, Harry Zhang +4
Robust autonomous navigation in environments with limited visibility remains a critical challenge in robotics. We present a novel approach that leverages Non-Line-of-Sight (NLOS) s…
NeST: Neural Stress Tensor Tomography by leveraging 3D Photoelasticity
Akshat Dave, Tianyi Zhang, Aaron Young +3
Photoelasticity enables full-field stress analysis in transparent objects through stress-induced birefringence. Existing techniques are limited to 2D slices and require destructive…
Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging
Manasi Muglikar, Siddharth Somasundaram, Akshat Dave +3
Traditional cameras face a trade-off between low-light performance and high-speed imaging: longer exposure times to capture sufficient light results in motion blur, whereas shorter…
DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images
Zaid Tasneem, Akshat Dave, Abhishek Singh +4
Neural radiance fields (NeRFs) show potential for transforming images captured worldwide into immersive 3D visual experiences. However, most of this captured visual data remains si…
SUNDIAL: 3D Satellite Understanding through Direct, Ambient, and Complex Lighting Decomposition
Nikhil Behari, Akshat Dave, Kushagra Tiwary +2
3D modeling from satellite imagery is essential in areas of environmental science, urban planning, agriculture, and disaster response. However, traditional 3D modeling techniques f…
Role of Transients in Two-Bounce Non-Line-of-Sight Imaging
Siddharth Somasundaram, Akshat Dave, Connor Henley +2
The goal of non-line-of-sight (NLOS) imaging is to image objects occluded from the camera's field of view using multiply scattered light. Recent works have demonstrated the feasibi…
ORCa: Glossy Objects as Radiance Field Cameras
Kushagra Tiwary, Akshat Dave, Nikhil Behari +3
Reflections on glossy objects contain valuable and hidden information about the surrounding environment. By converting these objects into cameras, we can unlock exciting applicatio…
PANDORA: Polarization-Aided Neural Decomposition Of Radiance
Akshat Dave, Yongyi Zhao, Ashok Veeraraghavan
Reconstructing an object's geometry and appearance from multiple images, also known as inverse rendering, is a fundamental problem in computer graphics and vision. Inverse renderin…
Thermal Image Processing via Physics-Inspired Deep Networks
Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan +1
We introduce DeepIR, a new thermal image processing framework that combines physically accurate sensor modeling with deep network-based image representation. Our key enabling obser…
Solving Inverse Computational Imaging Problems using Deep Pixel-level Prior
Akshat Dave, Anil Kumar Vadathya, Ramana Subramanyam +2
Signal reconstruction is a challenging aspect of computational imaging as it often involves solving ill-posed inverse problems. Recently, deep feed-forward neural networks have led…
IITMSAT Communications System : A LeanSat Design Approach
Akshay Gulati, Shubham Chavan, Joseph Samuel +10
IITMSAT is a student-built nano satellite mission of Indian Institute of Technology Madras, Chennai, India. The objective is to study the precipitation of high energy electrons and…
Compressive Image Recovery Using Recurrent Generative Model
Akshat Dave, Anil Kumar Vadathya, Kaushik Mitra
Reconstruction of signals from compressively sensed measurements is an ill-posed problem. In this paper, we leverage the recurrent generative model, RIDE, as an image prior for com…