1 citations · 4 across the 12 of their papers we have counts for
14 papers
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…
Radar2Shape: 3D Shape Reconstruction from High-Frequency Radar using Multiresolution Signed Distance Functions
Neel Sortur, Justin Goodwin, Purvik Patel +4
Determining the shape of 3D objects from high-frequency radar signals is analytically complex but critical for commercial and aerospace applications. Previous deep learning methods…
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…
Epi-NAF: Enhancing Neural Attenuation Fields for Limited-Angle CT with Epipolar Consistency Conditions
Daniel Gilo, Tzofi Klinghoffer, Or Litany
Neural field methods, initially successful in the inverse rendering domain, have recently been extended to CT reconstruction, marking a paradigm shift from traditional techniques.…
PlatoNeRF: 3D Reconstruction in Plato's Cave via Single-View Two-Bounce Lidar
Tzofi Klinghoffer, Xiaoyu Xiang, Siddharth Somasundaram +4
3D reconstruction from a single-view is challenging because of the ambiguity from monocular cues and lack of information about occluded regions. Neural radiance fields (NeRF), whil…
DISeR: Designing Imaging Systems with Reinforcement Learning
Tzofi Klinghoffer, Kushagra Tiwary, Nikhil Behari +2
Imaging systems consist of cameras to encode visual information about the world and perception models to interpret this encoding. Cameras contain (1) illumination sources, (2) opti…
Towards Viewpoint Robustness in Bird's Eye View Segmentation
Tzofi Klinghoffer, Jonah Philion, Wenzheng Chen +6
Autonomous vehicles (AV) require that neural networks used for perception be robust to different viewpoints if they are to be deployed across many types of vehicles without the rep…
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…
Physically Disentangled Representations
Tzofi Klinghoffer, Kushagra Tiwary, Arkadiusz Balata +2
State-of-the-art methods in generative representation learning yield semantic disentanglement, but typically do not consider physical scene parameters, such as geometry, albedo, li…
Physics vs. Learned Priors: Rethinking Camera and Algorithm Design for Task-Specific Imaging
Tzofi Klinghoffer, Siddharth Somasundaram, Kushagra Tiwary +1
Cameras were originally designed using physics-based heuristics to capture aesthetic images. In recent years, there has been a transformation in camera design from being purely phy…
Towards Learning Neural Representations from Shadows
Kushagra Tiwary, Tzofi Klinghoffer, Ramesh Raskar
We present a method that learns neural shadow fields which are neural scene representations that are only learnt from the shadows present in the scene. While traditional shape-from…
Self-Supervised Feature Extraction for 3D Axon Segmentation
Tzofi Klinghoffer, Peter Morales, Young-Gyun Park +3
Existing learning-based methods to automatically trace axons in 3D brain imagery often rely on manually annotated segmentation labels. Labeling is a labor-intensive process and is…
Feature Forwarding for Efficient Single Image Dehazing
Peter Morales, Tzofi Klinghoffer, Seung Jae Lee
Haze degrades content and obscures information of images, which can negatively impact vision-based decision-making in real-time systems. In this paper, we propose an efficient full…