Search Results for author: Joe Yue-Hei Ng

Found 8 papers, 1 papers with code

Beyond Short Snippets: Deep Networks for Video Classification

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.

Action Recognition Classification +4

ActionFlowNet: Learning Motion Representation for Action Recognition

no code implementations9 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.

Action Recognition Optical Flow Estimation +1

Generating Holistic 3D Scene Abstractions for Text-based Image Retrieval

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.

Image Retrieval Object +3

TAN: Temporal Aggregation Network for Dense Multi-label Action Recognition

no code implementations14 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.

Action Recognition Temporal Action Localization

FASON: First and Second Order Information Fusion Network for Texture Recognition

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.

EnsembleNet: End-to-End Optimization of Multi-headed Models

no code implementations24 May 2019 Hanhan Li, Joe Yue-Hei Ng, Paul Natsev

Ensembling is a universally useful approach to boost the performance of machine learning models.

OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI

no code implementations4 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.

Benchmarking

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