5 citations · 9 across the 7 of their papers we have counts for
15 papers
Exploring bidirectional bounds for minimax-training of Energy-based models
Cong Geng, Jia Wang, Li Chen +3
Energy-based models (EBMs) estimate unnormalized densities in an elegant framework, but they are generally difficult to train. Recent work has linked EBMs to generative adversarial…
Enhanced Deep Animation Video Interpolation
Wang Shen, Cheng Ming, Wenbo Bao +3
Existing learning-based frame interpolation algorithms extract consecutive frames from high-speed natural videos to train the model. Compared to natural videos, cartoon videos are…
A Coding Framework and Benchmark towards Low-Bitrate Video Understanding
Yuan Tian, Guo Lu, Yichao Yan +3
Video compression is indispensable to most video analysis systems. Despite saving transportation bandwidth, it also deteriorates downstream video understanding tasks, especially at…
Bounds all around: training energy-based models with bidirectional bounds
Cong Geng, Jia Wang, Zhiyong Gao +2
Energy-based models (EBMs) provide an elegant framework for density estimation, but they are notoriously difficult to train. Recent work has established links to generative adversa…
Self-Conditioned Probabilistic Learning of Video Rescaling
Yuan Tian, Guo Lu, Xiongkuo Min +4
Bicubic downscaling is a prevalent technique used to reduce the video storage burden or to accelerate the downstream processing speed. However, the inverse upscaling step is non-tr…
EAN: Event Adaptive Network for Enhanced Action Recognition
Yuan Tian, Yichao Yan, Guangtao Zhai +2
Efficiently modeling spatial-temporal information in videos is crucial for action recognition. To achieve this goal, state-of-the-art methods typically employ the convolution opera…