8 citations · 16 across the 10 of their papers we have counts for
10 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…
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…
Guided Speech Enhancement Network
Yang Yang, Shao-Fu Shih, Hakan Erdogan +5
High quality speech capture has been widely studied for both voice communication and human computer interface reasons. To improve the capture performance, we can often find multi-m…
Efficient Heterogeneous Video Segmentation at the Edge
Jamie Menjay Lin, Siargey Pisarchyk, Juhyun Lee +7
We introduce an efficient video segmentation system for resource-limited edge devices leveraging heterogeneous compute. Specifically, we design network models by searching across m…
Imposing Consistency for Optical Flow Estimation
Jisoo Jeong, Jamie Menjay Lin, Fatih Porikli +1
Imposing consistency through proxy tasks has been shown to enhance data-driven learning and enable self-supervision in various tasks. This paper introduces novel and effective cons…
Structured Convolutions for Efficient Neural Network Design
Yash Bhalgat, Yizhe Zhang, Jamie Lin +1
In this work, we tackle model efficiency by exploiting redundancy in the \textit{implicit structure} of the building blocks of convolutional neural networks. We start our analysis…
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices
Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin +3
Recent advances demonstrate that irregularly wired neural networks from Neural Architecture Search (NAS) and Random Wiring can not only automate the design of deep neural networks…