activity
20242026
most citedFutureDepth: Learning to Predict the Future Improves Video Depth Estimation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SNM-VFI: Symmetric Nonlinear Motion-Guided Generative Video Frame Interpolation

Jisoo Jeong, Hong Cai, Jamie Menjay Lin +5

We propose Symmetric Nonlinear Motion-guided Generative Video Frame Interpolation (SNM-VFI), a training-free framework for motion-controllable generative video frame interpolation…

cs.CV2025

ODG: Occupancy Prediction Using Dual Gaussians

Yunxiao Shi, Yinhao Zhu, Shizhong Han +4

Occupancy prediction infers fine-grained 3D geometry and semantics from camera images of the surrounding environment, making it a critical perception task for autonomous driving. E…

cs.CV2025

BePo: Dual Representation for 3D Occupancy Prediction

Yunxiao Shi, Hong Cai, Jisoo Jeong +4

3D occupancy infers fine-grained 3D geometry and semantics which is critical for autonomous driving. Most existing approaches carry high compute costs, requiring dense 3D feature v…

cs.CV2024★ 1 cited

FutureDepth: Learning to Predict the Future Improves Video Depth Estimation

Rajeev Yasarla, Manish Kumar Singh, Hong Cai +6

In this paper, we propose a novel video depth estimation approach, FutureDepth, which enables the model to implicitly leverage multi-frame and motion cues to improve depth estimati…

cs.CV2024

Neural Mesh Fusion: Unsupervised 3D Planar Surface Understanding

Farhad G. Zanjani, Hong Cai, Yinhao Zhu +2

This paper presents Neural Mesh Fusion (NMF), an efficient approach for joint optimization of polygon mesh from multi-view image observations and unsupervised 3D planar-surface par…