1 citations · 1 across the 8 of their papers we have counts for
9 papers
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…
SciFlow: Semantic Cross Interference for Self-Supervised Optical Flow Domain Generalization
Jamie Menjay Lin, Jisoo Jeong, Hong Cai +2
Motions of objects and scenes carry essential intelligence in video understanding, offering rich cues for interpreting dynamic settings and interactions. Due to the cost and scarci…
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…
Learning Optical Flow Field via Neural Ordinary Differential Equation
Leyla Mirvakhabova, Hong Cai, Jisoo Jeong +3
Recent works on optical flow estimation use neural networks to predict the flow field that maps positions of one image to positions of the other. These networks consist of a featur…
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…
Improving Optical Flow and Stereo Depth Estimation by Leveraging Uncertainty-Based Learning Difficulties
Jisoo Jeong, Hong Cai, Jamie Menjay Lin +1
Conventional training for optical flow and stereo depth models typically employs a uniform loss function across all pixels. However, this one-size-fits-all approach often overlooks…
SciFlow: Empowering Lightweight Optical Flow Models with Self-Cleaning Iterations
Jamie Menjay Lin, Jisoo Jeong, Hong Cai +3
Optical flow estimation is crucial to a variety of vision tasks. Despite substantial recent advancements, achieving real-time on-device optical flow estimation remains a complex ch…
OCAI: Improving Optical Flow Estimation by Occlusion and Consistency Aware Interpolation
Jisoo Jeong, Hong Cai, Risheek Garrepalli +3
The scarcity of ground-truth labels poses one major challenge in developing optical flow estimation models that are both generalizable and robust. While current methods rely on dat…
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…