Search Results for author: Frederick Tung

Found 15 papers, 5 papers with code

Where and when to look? Spatial-temporal attention for action recognition in videos

no code implementations ICLR 2019 Lili Meng, Bo Zhao, Bo Chang, Gao Huang, Frederick Tung, Leonid Sigal

Our model is efficient, as it proposes a separable spatio-temporal mechanism for video attention, while being able to identify important parts of the video both spatially and temporally.

Action Recognition Action Recognition In Videos +1

Gumbel-Softmax Selective Networks

no code implementations19 Nov 2022 Mahmoud Salem, Mohamed Osama Ahmed, Frederick Tung, Gabriel Oliveira

This commonly encountered operational context calls for principled techniques for training ML models with the option to abstain from predicting when uncertain.

RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression

1 code implementation30 May 2022 Yu Gong, Greg Mori, Frederick Tung

Data imbalance, in which a plurality of the data samples come from a small proportion of labels, poses a challenge in training deep neural networks.

Inductive Bias regression +2


no code implementations29 Sep 2021 Golara Javadi, Frederick Tung, Gabriel L. Oliveira

Parameter sharing approaches for deep multi-task learning share a common intuition: for a single network to perform multiple prediction tasks, the network needs to support multiple specialized execution paths.

Multi-Task Learning

Heterogeneous Multi-task Learning with Expert Diversity

1 code implementation20 Jun 2021 Raquel Aoki, Frederick Tung, Gabriel L. Oliveira

In contrast to single-task learning, in which a separate model is trained for each target, multi-task learning (MTL) optimizes a single model to predict multiple related targets simultaneously.

Multi-Task Learning

Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation

no code implementations ECCV 2020 Mengyao Zhai, Lei Chen, JiaWei He, Megha Nawhal, Frederick Tung, Greg Mori

In contrast, we propose a parameter efficient framework, Piggyback GAN, which learns the current task by building a set of convolutional and deconvolutional filters that are factorized into filters of the models trained on previous tasks.

Learning Discriminative Prototypes with Dynamic Time Warping

1 code implementation CVPR 2021 Xiaobin Chang, Frederick Tung, Greg Mori

We propose Discriminative Prototype DTW (DP-DTW), a novel method to learn class-specific discriminative prototypes for temporal recognition tasks.

Action Segmentation Dynamic Time Warping +2

Similarity-Preserving Knowledge Distillation

1 code implementation ICCV 2019 Frederick Tung, Greg Mori

Knowledge distillation is a widely applicable technique for training a student neural network under the guidance of a trained teacher network.

Knowledge Distillation Neural Network Compression

Constraint-Aware Deep Neural Network Compression

no code implementations ECCV 2018 Changan Chen, Frederick Tung, Naveen Vedula, Greg Mori

Deep neural network compression has the potential to bring modern resource-hungry deep networks to resource-limited devices.

Neural Network Compression Pedestrian Detection

CLIP-Q: Deep Network Compression Learning by In-Parallel Pruning-Quantization

no code implementations CVPR 2018 Frederick Tung, Greg Mori

This allows us to take advantage of the complementary nature of pruning and quantization and to recover from premature pruning errors, which is not possible with current two-stage approaches.

Image Classification Network Pruning +3

Exploiting Points and Lines in Regression Forests for RGB-D Camera Relocalization

no code implementations28 Oct 2017 Lili Meng, Frederick Tung, James J. Little, Julien Valentin, Clarence de Silva

Camera relocalization plays a vital role in many robotics and computer vision tasks, such as global localization, recovery from tracking failure and loop closure detection.

Camera Relocalization Loop Closure Detection +1

Multi-level Residual Networks from Dynamical Systems View

no code implementations ICLR 2018 Bo Chang, Lili Meng, Eldad Haber, Frederick Tung, David Begert

Deep residual networks (ResNets) and their variants are widely used in many computer vision applications and natural language processing tasks.

General Classification Image Classification

Backtracking Regression Forests for Accurate Camera Relocalization

1 code implementation22 Oct 2017 Lili Meng, Jianhui Chen, Frederick Tung, James J. Little, Julien Valentin, Clarence W. de Silva

Camera relocalization plays a vital role in many robotics and computer vision tasks, such as global localization, recovery from tracking failure, and loop closure detection.

Camera Relocalization Loop Closure Detection +2

Fine-Pruning: Joint Fine-Tuning and Compression of a Convolutional Network with Bayesian Optimization

no code implementations28 Jul 2017 Frederick Tung, Srikanth Muralidharan, Greg Mori

When approaching a novel visual recognition problem in a specialized image domain, a common strategy is to start with a pre-trained deep neural network and fine-tune it to the specialized domain.

Network Pruning

Learning Person Trajectory Representations for Team Activity Analysis

no code implementations3 Jun 2017 Nazanin Mehrasa, Yatao Zhong, Frederick Tung, Luke Bornn, Greg Mori

Activity analysis in which multiple people interact across a large space is challenging due to the interplay of individual actions and collective group dynamics.

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