4 citations · 5 across the 3 of their papers we have counts for
11 papers
Temporal Relevance Analysis for Video Action Models
Quanfu Fan, Donghyun Kim, Chun-Fu +4
In this paper, we provide a deep analysis of temporal modeling for action recognition, an important but underexplored problem in the literature. We first propose a new approach to…
CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection
Quanfu Fan, Yilai Li, Yuguang Yao +4
Single-particle cryo-electron microscopy (cryo-EM) has become one of the mainstream structural biology techniques because of its ability to determine high-resolution structures of…
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Rameswar Panda, Chun-Fu Chen, Quanfu Fan +4
Multi-modal learning, which focuses on utilizing various modalities to improve the performance of a model, is widely used in video recognition. While traditional multi-modal learni…
Generating Adversarial Computer Programs using Optimized Obfuscations
Shashank Srikant, Sijia Liu, Tamara Mitrovska +4
Machine learning (ML) models that learn and predict properties of computer programs are increasingly being adopted and deployed. These models have demonstrated success in applicati…
CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
Chun-Fu Chen, Quanfu Fan, Rameswar Panda
The recently developed vision transformer (ViT) has achieved promising results on image classification compared to convolutional neural networks. Inspired by this, in this paper, w…
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
Chun-Fu Chen, Rameswar Panda, Kandan Ramakrishnan +4
In recent years, a number of approaches based on 2D or 3D convolutional neural networks (CNN) have emerged for video action recognition, achieving state-of-the-art results on sever…