activity
20212026
most citedADCNet: Learning from Raw Radar Data via Distillation

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

OV3D-Bench: A Diagnostic Benchmark for Open-Vocabulary Monocular 3D Detection

Mariia Gladkova, Neehar Peri, Ishan Khatri +2

Open-vocabulary monocular 3D detectors report strong in-domain performance, but each evaluates under a different protocol, several rely on per-image category oracles unavailable at…

cs.CV2025

UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles

Siyi Li, Qingwen Zhang, Ishan Khatri +4

LiDAR scene flow is the task of estimating per-point 3D motion between consecutive point clouds. Recent methods achieve centimeter-level accuracy on popular autonomous vehicle (AV)…

cs.CV2024

Neural Eulerian Scene Flow Fields

Kyle Vedder, Neehar Peri, Ishan Khatri +7

We reframe scene flow as the task of estimating a continuous space-time ODE that describes motion for an entire observation sequence, represented with a neural prior. Our method, E…

cs.CV2024

I Can't Believe It's Not Scene Flow!

Ishan Khatri, Kyle Vedder, Neehar Peri +2

Current scene flow methods broadly fail to describe motion on small objects, and current scene flow evaluation protocols hide this failure by averaging over many points, with most…

cs.CV2023

ZeroFlow: Scalable Scene Flow via Distillation

Kyle Vedder, Neehar Peri, Nathaniel Chodosh +6

Scene flow estimation is the task of describing the 3D motion field between temporally successive point clouds. State-of-the-art methods use strong priors and test-time optimizatio…

eess.SP2023★ 1 cited

ADCNet: Learning from Raw Radar Data via Distillation

Bo Yang, Ishan Khatri, Michael Happold +1

As autonomous vehicles and advanced driving assistance systems have entered wider deployment, there is an increased interest in building robust perception systems using radars. Rad…

cs.RO2021

Agent-aware State Estimation in Autonomous Vehicles

Shane Parr, Ishan Khatri, Justin Svegliato +1

Autonomous systems often operate in environments where the behavior of multiple agents is coordinated by a shared global state. Reliable estimation of the global state is thus crit…