activity
20232026
most citedControlling diverse robots by inferring Jacobian fields with deep networks

12 citations · 22 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

Visual Cue Guided Video Planning for Generalizable Robot Navigation

Hojin Lee, Sizhe Lester Li, Maximilian Hilger +4

Generative video models can serve as a promising backbone for robot navigation by predicting future observations as video plans. Recent approaches often condition video planning on…

cs.RO2026

Turning Video Models into Generalist Robot Policies

Sizhe Lester Li, Evan Kim, Xingjian Bai +4

Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across embodiments and environments.…

cs.LG2026

Conditional Rectified Flow-based End-to-End Rapid Seismic Inversion Method

Haofei Xu, Wei Cheng, Sizhe Li +1

Seismic inversion is a core problem in geophysical exploration, where traditional methods suffer from high computational costs and are susceptible to initial model dependence. In r…

cs.RO2024★ 12 cited

Controlling diverse robots by inferring Jacobian fields with deep networks

Sizhe Lester Li, Annan Zhang, Boyuan Chen +4

Mirroring the complex structures and diverse functions of natural organisms is a long-standing challenge in robotics. Modern fabrication techniques have greatly expanded the feasib…

cs.CV2023★ 10 cited

pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction

David Charatan, Sizhe Li, Andrea Tagliasacchi +1

We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-ti…