15 citations · 47 across the 14 of their papers we have counts for
14 papers
WFTNet: Exploiting Global and Local Periodicity in Long-term Time Series Forecasting
Peiyuan Liu, Beiliang Wu, Naiqi Li +5
Recent CNN and Transformer-based models tried to utilize frequency and periodicity information for long-term time series forecasting. However, most existing work is based on Fourie…
One-stage Low-resolution Text Recognition with High-resolution Knowledge Transfer
Hang Guo, Tao Dai, Mingyan Zhu +4
Recognizing characters from low-resolution (LR) text images poses a significant challenge due to the information deficiency as well as the noise and blur in low-quality images. Cur…
Towards Robust Scene Text Image Super-resolution via Explicit Location Enhancement
Hang Guo, Tao Dai, Guanghao Meng +1
Scene text image super-resolution (STISR), aiming to improve image quality while boosting downstream scene text recognition accuracy, has recently achieved great success. However,…
Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models
Yaohua Zha, Jinpeng Wang, Tao Dai +3
Pre-trained point cloud models have found extensive applications in 3D understanding tasks like object classification and part segmentation. However, the prevailing strategy of ful…
Towards Effective Image Manipulation Detection with Proposal Contrastive Learning
Yuyuan Zeng, Bowen Zhao, Shanzhao Qiu +2
Deep models have been widely and successfully used in image manipulation detection, which aims to classify tampered images and localize tampered regions. Most existing methods main…
Learned Distributed Image Compression with Multi-Scale Patch Matching in Feature Domain
Yujun Huang, Bin Chen, Shiyu Qin +4
Beyond achieving higher compression efficiency over classical image compression codecs, deep image compression is expected to be improved with additional side information, e.g., an…
VLMAE: Vision-Language Masked Autoencoder
Sunan He, Taian Guo, Tao Dai +4
Image and language modeling is of crucial importance for vision-language pre-training (VLP), which aims to learn multi-modal representations from large-scale paired image-text data…
Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolution
Hongwei Li, Tao Dai, Yiming Li +2
Image representation is critical for many visual tasks. Instead of representing images discretely with 2D arrays of pixels, a recent study, namely local implicit image function (LI…
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer
Sunan He, Taian Guo, Tao Dai +3
Real-world recognition system often encounters the challenge of unseen labels. To identify such unseen labels, multi-label zero-shot learning (ML-ZSL) focuses on transferring knowl…
A Comparative Study of Feature Expansion Unit for 3D Point Cloud Upsampling
Qiang Li, Tao Dai, Shu-Tao Xia
Recently, deep learning methods have shown great success in 3D point cloud upsampling. Among these methods, many feature expansion units were proposed to complete point expansion a…
PHPQ: Pyramid Hybrid Pooling Quantization for Efficient Fine-Grained Image Retrieval
Ziyun Zeng, Jinpeng Wang, Bin Chen +3
Deep hashing approaches, including deep quantization and deep binary hashing, have become a common solution to large-scale image retrieval due to their high computation and storage…
Contrastive Quantization with Code Memory for Unsupervised Image Retrieval
Jinpeng Wang, Ziyun Zeng, Bin Chen +2
The high efficiency in computation and storage makes hashing (including binary hashing and quantization) a common strategy in large-scale retrieval systems. To alleviate the relian…
JSRT: James-Stein Regression Tree
Xingchun Xiang, Qingtao Tang, Huaixuan Zhang +3
Regression tree (RT) has been widely used in machine learning and data mining community. Given a target data for prediction, a regression tree is first constructed based on a train…
Adversarial Attack on Deep Product Quantization Network for Image Retrieval
Yan Feng, Bin Chen, Tao Dai +1
Deep product quantization network (DPQN) has recently received much attention in fast image retrieval tasks due to its efficiency of encoding high-dimensional visual features espec…