348 citations · 562 across the 3 of their papers we have counts for
3 papers
cs.AI2025
What We Don't C: Manifold Disentanglement for Structured Discovery
Brian Rogers, Micah Bowles, Chris J. Lintott +3
Accessing information in learned representations is critical for annotation, discovery, and data filtering in disciplines where high-dimensional datasets are common. We introduce W…
cs.CV2017★ 214 cited
A Closer Look at Spatiotemporal Convolutions for Action Recognition
Du Tran, Heng Wang, Lorenzo Torresani +3
In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition. Our motivation stems from the observation th…
cs.CV2017★ 348 cited
ConvNet Architecture Search for Spatiotemporal Feature Learning
Du Tran, Jamie Ray, Zheng Shou +2
Learning image representations with ConvNets by pre-training on ImageNet has proven useful across many visual understanding tasks including object detection, semantic segmentation,…