77 citations · 253 across the 14 of their papers we have counts for
14 papers
Parameter-Efficient Transfer Learning for Remote Sensing Image-Text Retrieval
Yuan Yuan, Yang Zhan, Zhitong Xiong
Vision-and-language pre-training (VLP) models have experienced a surge in popularity recently. By fine-tuning them on specific datasets, significant performance improvements have b…
Unsupervised Learning for Human Sensing Using Radio Signals
Tianhong Li, Lijie Fan, Yuan Yuan +1
There is a growing literature demonstrating the feasibility of using Radio Frequency (RF) signals to enable key computer vision tasks in the presence of occlusions and poor lightin…
Targeted Supervised Contrastive Learning for Long-Tailed Recognition
Tianhong Li, Peng Cao, Yuan Yuan +5
Real-world data often exhibits long tail distributions with heavy class imbalance, where the majority classes can dominate the training process and alter the decision boundaries of…
Addressing Feature Suppression in Unsupervised Visual Representations
Tianhong Li, Lijie Fan, Yuan Yuan +5
Contrastive learning is one of the fastest growing research areas in machine learning due to its ability to learn useful representations without labeled data. However, contrastive…
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo
Yueming Lyu, Yuan Yuan, Ivor W. Tsang
Quasi-Monte Carlo (QMC) is an essential tool for integral approximation, Bayesian inference, and sampling for simulation in science, etc. In the QMC area, the rank-1 lattice is imp…
In-Home Daily-Life Captioning Using Radio Signals
Lijie Fan, Tianhong Li, Yuan Yuan +1
This paper aims to caption daily life --i.e., to create a textual description of people's activities and interactions with objects in their homes. Addressing this problem requires…
Learning Longterm Representations for Person Re-Identification Using Radio Signals
Lijie Fan, Tianhong Li, Rongyao Fang +3
Person Re-Identification (ReID) aims to recognize a person-of-interest across different places and times. Existing ReID methods rely on images or videos collected using RGB cameras…
Neuron Linear Transformation: Modeling the Domain Shift for Crowd Counting
Qi Wang, Tao Han, Junyu Gao +1
Cross-domain crowd counting (CDCC) is a hot topic due to its importance in public safety. The purpose of CDCC is to alleviate the domain shift between the source and target domain.…
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance
Junyu Gao, Yuan Yuan, Qi Wang
With the development of deep neural networks, the performance of crowd counting and pixel-wise density estimation are continually being refreshed. Despite this, there are still two…
Marginalized Average Attentional Network for Weakly-Supervised Learning
Yuan Yuan, Yueming Lyu, Xi Shen +2
In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most sali…
Memory-Augmented Temporal Dynamic Learning for Action Recognition
Yuan Yuan, Dong Wang, Qi Wang
Human actions captured in video sequences contain two crucial factors for action recognition, i.e., visual appearance and motion dynamics. To model these two aspects, Convolutional…
Learning from Synthetic Data for Crowd Counting in the Wild
Qi Wang, Junyu Gao, Wei Lin +1
Recently, counting the number of people for crowd scenes is a hot topic because of its widespread applications (e.g. video surveillance, public security). It is a difficult task in…
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
Yuan Yuan, Xiaodan Liang, Xiaolong Wang +2
In this paper, we investigate a weakly-supervised object detection framework. Most existing frameworks focus on using static images to learn object detectors. However, these detect…
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading
Chunlin Tian, Weijun Ji
The Aduio-visual Speech Recognition (AVSR) which employs both the video and audio information to do Automatic Speech Recognition (ASR) is one of the application of multimodal leani…