activity
20192025
most citedVisual Physics: Discovering Physical Laws from Videos

5 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV2025

RnGCam: High-speed video from rolling & global shutter measurements

Kevin Tandi, Xiang Dai, Chinmay Talegaonkar +2

Compressive video capture encodes a short high-speed video into a single measurement using a low-speed sensor, then computationally reconstructs the original video. Prior implement…

cs.CV2025

Repurposing Marigold for Zero-Shot Metric Depth Estimation via Defocus Blur Cues

Chinmay Talegaonkar, Nikhil Gandudi Suresh, Zachary Novack +3

Recent monocular metric depth estimation (MMDE) methods have made notable progress towards zero-shot generalization. However, they still exhibit a significant performance drop on o…

cs.CV2024

Volumetrically Consistent 3D Gaussian Rasterization

Chinmay Talegaonkar, Yash Belhe, Ravi Ramamoorthi +1

Recently, 3D Gaussian Splatting (3DGS) has enabled photorealistic view synthesis at high inference speeds. However, its splatting-based rendering model makes several approximations…

cs.CV2024

Pose Estimation of Buried Deep-Sea Objects using 3D Vision Deep Learning Models

Jerry Yan, Chinmay Talegaonkar, Nicholas Antipa +2

We present an approach for pose and burial fraction estimation of debris field barrels found on the seabed in the Southern California San Pedro Basin. Our computational workflow le…

cs.CV20195 cited

Visual Physics: Discovering Physical Laws from Videos

Pradyumna Chari, Chinmay Talegaonkar, Yunhao Ba +1

In this paper, we teach a machine to discover the laws of physics from video streams. We assume no prior knowledge of physics, beyond a temporal stream of bounding boxes. The probl…