no code implementations • 4 Apr 2023 • Joe Yue-Hei Ng, Kevin McCloskey, Jian Cui, Vincent R. Meijer, Erica Brand, Aaron Sarna, Nita Goyal, Christopher Van Arsdale, Scott Geraedts
Contrails (condensation trails) are line-shaped ice clouds caused by aircraft and are likely the largest contributor of aviation-induced climate change.
no code implementations • 24 May 2019 • Hanhan Li, Joe Yue-Hei Ng, Paul Natsev
Ensembling is a universally useful approach to boost the performance of machine learning models.
no code implementations • 14 Dec 2018 • Xiyang Dai, Bharat Singh, Joe Yue-Hei Ng, Larry S. Davis
We present Temporal Aggregation Network (TAN) which decomposes 3D convolutions into spatial and temporal aggregation blocks.
no code implementations • CVPR 2017 • Xiyang Dai, Joe Yue-Hei Ng, Larry S. Davis
We then build a multi-level deep architecture to exploit the first and second order information within different convolutional layers.
no code implementations • 9 Dec 2016 • Joe Yue-Hei Ng, Jonghyun Choi, Jan Neumann, Larry S. Davis
Even with the recent advances in convolutional neural networks (CNN) in various visual recognition tasks, the state-of-the-art action recognition system still relies on hand crafted motion feature such as optical flow to achieve the best performance.
Ranked #69 on Action Recognition on HMDB-51
no code implementations • CVPR 2017 • Ang Li, Jin Sun, Joe Yue-Hei Ng, Ruichi Yu, Vlad I. Morariu, Larry S. Davis
Since interactions between objects can be reduced to a limited set of atomic spatial relations in 3D, we study the possibility of inferring 3D structure from a text description rather than an image, applying physical relation models to synthesize holistic 3D abstract object layouts satisfying the spatial constraints present in a textual description.
no code implementations • 20 Apr 2015 • Joe Yue-Hei Ng, Fan Yang, Larry S. Davis
Deep convolutional neural networks have been successfully applied to image classification tasks.
1 code implementation • CVPR 2015 • Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici
Convolutional neural networks (CNNs) have been extensively applied for image recognition problems giving state-of-the-art results on recognition, detection, segmentation and retrieval.
Ranked #5 on Action Recognition on Sports-1M