22 citations · 92 across the 15 of their papers we have counts for
15 papers
Prototypical Transformer as Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun +9
In this work, we introduce the Prototypical Transformer (ProtoFormer), a general and unified framework that approaches various motion tasks from a prototype perspective. ProtoForme…
STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical Question-Answering
Guohao Sun, Can Qin, Huazhu Fu +2
Large Vision-Language Models (LVLMs) have shown significant potential in assisting medical diagnosis by leveraging extensive biomedical datasets. However, the advancement of medica…
Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval
Jiamian Wang, Guohao Sun, Pichao Wang +5
The increasing prevalence of video clips has sparked growing interest in text-video retrieval. Recent advances focus on establishing a joint embedding space for text and video, rel…
Parameter-Efficient Masking Networks
Yue Bai, Huan Wang, Xu Ma +3
A deeper network structure generally handles more complicated non-linearity and performs more competitively. Nowadays, advanced network designs often contain a large number of repe…
Dual Lottery Ticket Hypothesis
Yue Bai, Huan Wang, Zhiqiang Tao +2
Fully exploiting the learning capacity of neural networks requires overparameterized dense networks. On the other side, directly training sparse neural networks typically results i…
Adversarial Memory Networks for Action Prediction
Zhiqiang Tao, Yue Bai, Handong Zhao +3
Action prediction aims to infer the forthcoming human action with partially-observed videos, which is a challenging task due to the limited information underlying early observation…
A Simple and Efficient Reconstruction Backbone for Snapshot Compressive Imaging
Jiamian Wang, Yulun Zhang, Xin Yuan +2
The emerging technology of snapshot compressive imaging (SCI) enables capturing high dimensional (HD) data in an efficient way. It is generally implemented by two components: an op…
Automated Graph Learning via Population Based Self-Tuning GCN
Ronghang Zhu, Zhiqiang Tao, Yaliang Li +1
Owing to the remarkable capability of extracting effective graph embeddings, graph convolutional network (GCN) and its variants have been successfully applied to a broad range of t…
Collaborative Attention Mechanism for Multi-View Action Recognition
Yue Bai, Zhiqiang Tao, Lichen Wang +3
Multi-view action recognition (MVAR) leverages complementary temporal information from different views to improve the learning performance. Obtaining informative view-specific repr…
Learnable Subspace Clustering
Jun Li, Hongfu Liu, Zhiqiang Tao +2
This paper studies the large-scale subspace clustering (LSSC) problem with million data points. Many popular subspace clustering methods cannot directly handle the LSSC problem alt…
Generative Partial Multi-View Clustering
Qianqian Wang, Zhengming Ding, Zhiqiang Tao +2
Nowadays, with the rapid development of data collection sources and feature extraction methods, multi-view data are getting easy to obtain and have received increasing research att…
Automated Relational Meta-learning
Huaxiu Yao, Xian Wu, Zhiqiang Tao +4
In order to efficiently learn with small amount of data on new tasks, meta-learning transfers knowledge learned from previous tasks to the new ones. However, a critical challenge i…
Correlative Channel-Aware Fusion for Multi-View Time Series Classification
Yue Bai, Lichen Wang, Zhiqiang Tao +2
Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on f…
Consensus Clustering: An Embedding Perspective, Extension and Beyond
Hongfu Liu, Zhiqiang Tao, Zhengming Ding
Consensus clustering fuses diverse basic partitions (i.e., clustering results obtained from conventional clustering methods) into an integrated one, which has attracted increasing…
Segmentation Guided Image-to-Image Translation with Adversarial Networks
Songyao Jiang, Zhiqiang Tao, Yun Fu
Recently image-to-image translation has received increasing attention, which aims to map images in one domain to another specific one. Existing methods mainly solve this task via a…