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04/28/2023
Improve Video Representation with Temporal Adversarial Augmentation
Recent works reveal that adversarial augmentation benefits the generaliz...
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10/28/2022
Grafting Vision Transformers
Vision Transformers (ViTs) have recently become the state-of-the-art acr...
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08/03/2022
Augmentation Learning for Semi-Supervised Classification
Recently, a number of new Semi-Supervised Learning methods have emerged....
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06/13/2022
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Current deep neural networks (DNNs) are vulnerable to adversarial attack...
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04/25/2022
Temporal Relevance Analysis for Video Action Models
In this paper, we provide a deep analysis of temporal modeling for actio...
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04/15/2022
CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection
Single-particle cryo-electron microscopy (cryo-EM) has become one of the...
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06/26/2021
An Image Classifier Can Suffice For Video Understanding
We propose a new perspective on video understanding by casting the video...
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06/04/2021
RegionViT: Regional-to-Local Attention for Vision Transformers
Vision transformer (ViT) has recently showed its strong capability in ac...
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05/11/2021
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Multi-modal learning, which focuses on utilizing various modalities to i...
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03/27/2021
CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
The recently developed vision transformer (ViT) has achieved promising r...
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03/18/2021
Generating Adversarial Computer Programs using Optimized Obfuscations
Machine learning (ML) models that learn and predict properties of comput...
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10/22/2020
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
In recent years, a number of approaches based on 2D CNNs and 3D CNNs hav...
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12/02/2019
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation
Current state-of-the-art models for video action recognition are mostly ...
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10/18/2019
Evading Real-Time Person Detectors by Adversarial T-shirt
It is known that deep neural networks (DNNs) could be vulnerable to adve...
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09/10/2019
Reasoning About Human-Object Interactions Through Dual Attention Networks
Objects are entities we act upon, where the functionality of an object i...
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04/03/2019
Interpreting Adversarial Examples by Activation Promotion and Suppression
It is widely known that convolutional neural networks (CNNs) are vulnera...
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08/07/2018
Efficient Fusion of Sparse and Complementary Convolutions for Object Recognition and Detection
We propose a new method for exploiting sparsity in convolutional kernels...
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07/10/2018
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition
In this paper, we propose a novel Convolutional Neural Network (CNN) arc...
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01/09/2018
