Search Results for author: Tao Dai

Found 33 papers, 17 papers with code

Hierarchical Features Matter: A Deep Exploration of GAN Priors for Improved Dataset Distillation

no code implementations9 Jun 2024 Xinhao Zhong, Hao Fang, Bin Chen, Xulin Gu, Tao Dai, Meikang Qiu, Shu-Tao Xia

Dataset distillation is an emerging dataset reduction method, which condenses large-scale datasets while maintaining task accuracy.

Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting

1 code implementation6 Jun 2024 Yifan Hu, Peiyuan Liu, Peng Zhu, Dawei Cheng, Tao Dai

Transformer-based and MLP-based methods have emerged as leading approaches in time series forecasting (TSF).

Computational Efficiency Data Integration +2

LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling

no code implementations27 May 2024 Yaohua Zha, Naiqi Li, Yanzi Wang, Tao Dai, Hang Guo, Bin Chen, Zhi Wang, Zhihao Ouyang, Shu-Tao Xia

Considering the varying information density between masked and unmasked patches in the decoder inputs of MPM, we introduce a locally constrained Mamba-based decoder.

Decoder

GMMFormer v2: An Uncertainty-aware Framework for Partially Relevant Video Retrieval

1 code implementation22 May 2024 Yuting Wang, Jinpeng Wang, Bin Chen, Tao Dai, Ruisheng Luo, Shu-Tao Xia

Given a text query, partially relevant video retrieval (PRVR) aims to retrieve untrimmed videos containing relevant moments.

Partially Relevant Video Retrieval Retrieval +1

Boundary-aware Decoupled Flow Networks for Realistic Extreme Rescaling

no code implementations5 May 2024 Jinmin Li, Tao Dai, Jingyun Zhang, Kang Liu, Jun Wang, Shaoming Wang, Shu-Tao Xia, rizen guo

Recently developed generative methods, including invertible rescaling network (IRN) based and generative adversarial network (GAN) based methods, have demonstrated exceptional performance in image rescaling.

Generative Adversarial Network SSIM

Invertible Residual Rescaling Models

no code implementations5 May 2024 Jinmin Li, Tao Dai, Yaohua Zha, Yilu Luo, Longfei Lu, Bin Chen, Zhi Wang, Shu-Tao Xia, Jingyun Zhang

To address this issue, we propose Invertible Residual Rescaling Models (IRRM) for image rescaling by learning a bijection between a high-resolution image and its low-resolution counterpart with a specific distribution.

RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction

1 code implementation2 Apr 2024 Yushen Li, Jinpeng Wang, Tao Dai, Jieming Zhu, Jun Yuan, Rui Zhang, Shu-Tao Xia

Predicting click-through rates (CTR) is a fundamental task for Web applications, where a key issue is to devise effective models for feature interactions.

Click-Through Rate Prediction Retrieval

CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning

2 code implementations12 Mar 2024 Peiyuan Liu, Hang Guo, Tao Dai, Naiqi Li, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia

Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great superiority, especially with limited temporal data.

Knowledge Distillation Multivariate Time Series Forecasting +2

MambaIR: A Simple Baseline for Image Restoration with State-Space Model

1 code implementation23 Feb 2024 Hang Guo, Jinmin Li, Tao Dai, Zhihao Ouyang, Xudong Ren, Shu-Tao Xia

In this way, our MambaIR takes advantage of the local pixel similarity and reduces the channel redundancy.

Image Restoration

SpirDet: Towards Efficient, Accurate and Lightweight Infrared Small Target Detector

no code implementations8 Feb 2024 Qianchen Mao, Qiang Li, Bingshu Wang, Yongjun Zhang, Tao Dai, C. L. Philip Chen

To tackle this challenge, we propose SpirDet, a novel approach for efficient detection of infrared small targets.

Decoder

Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders

1 code implementation17 Dec 2023 Yaohua Zha, Huizhen Ji, Jinmin Li, Rongsheng Li, Tao Dai, Bin Chen, Zhi Wang, Shu-Tao Xia

Specifically, to learn more compact features, a share-parameter Transformer encoder is introduced to extract point features from the global and local unmasked patches obtained by global random and local block mask strategies, followed by a specific decoder to reconstruct.

Few-Shot 3D Point Cloud Classification

AdaptIR: Parameter Efficient Multi-task Adaptation for Pre-trained Image Restoration Models

1 code implementation12 Dec 2023 Hang Guo, Tao Dai, Yuanchao Bai, Bin Chen, Shu-Tao Xia, Zexuan Zhu

Recently, Parameter Efficient Transfer Learning (PETL) offers an efficient alternative solution to full fine-tuning, yet still faces great challenges for pre-trained image restoration models, due to the diversity of different degradations.

Image Denoising Image Restoration +1

Perceptual Image Compression with Cooperative Cross-Modal Side Information

no code implementations23 Nov 2023 Shiyu Qin, Bin Chen, Yujun Huang, Baoyi An, Tao Dai, Shu-Tao Xia

The explosion of data has resulted in more and more associated text being transmitted along with images.

Decoder Image Compression +1

One-stage Low-resolution Text Recognition with High-resolution Knowledge Transfer

1 code implementation5 Aug 2023 Hang Guo, Tao Dai, Mingyan Zhu, Guanghao Meng, Bin Chen, Zhi Wang, Shu-Tao Xia

Current solutions for low-resolution text recognition (LTR) typically rely on a two-stage pipeline that involves super-resolution as the first stage followed by the second-stage recognition.

Contrastive Learning Knowledge Distillation +2

Towards Robust Scene Text Image Super-resolution via Explicit Location Enhancement

1 code implementation19 Jul 2023 Hang Guo, Tao Dai, Guanghao Meng, Shu-Tao Xia

Scene text image super-resolution (STISR), aiming to improve image quality while boosting downstream scene text recognition accuracy, has recently achieved great success.

Image Super-Resolution LEMMA +1

Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model

no code implementations ICCV 2023 Xinyi Zhang, Naiqi Li, Jiawei Li, Tao Dai, Yong Jiang, Shu-Tao Xia

Unsupervised surface anomaly detection aims at discovering and localizing anomalous patterns using only anomaly-free training samples.

Unsupervised Anomaly Detection

Towards Effective Image Manipulation Detection with Proposal Contrastive Learning

1 code implementation16 Oct 2022 Yuyuan Zeng, Bowen Zhao, Shanzhao Qiu, Tao Dai, Shu-Tao Xia

Most existing methods mainly focus on extracting global features from tampered images, while neglecting the relationships of local features between tampered and authentic regions within a single tampered image.

Contrastive Learning Image Manipulation +1

Learned Distributed Image Compression with Multi-Scale Patch Matching in Feature Domain

no code implementations6 Sep 2022 Yujun Huang, Bin Chen, Shiyu Qin, Jiawei Li, YaoWei Wang, Tao Dai, Shu-Tao Xia

Specifically, MSFDPM consists of a side information feature extractor, a multi-scale feature domain patch matching module, and a multi-scale feature fusion network.

Decoder Image Compression +1

VLMAE: Vision-Language Masked Autoencoder

no code implementations19 Aug 2022 Sunan He, Taian Guo, Tao Dai, Ruizhi Qiao, Chen Wu, Xiujun Shu, Bo Ren

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.

Language Modelling Question Answering +4

Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer

1 code implementation5 Jul 2022 Sunan He, Taian Guo, Tao Dai, Ruizhi Qiao, Bo Ren, Shu-Tao Xia

Specifically, our method exploits multi-modal knowledge of image-text pairs based on a vision and language pre-training (VLP) model.

Image-text matching Knowledge Distillation +7

Contrastive Quantization with Code Memory for Unsupervised Image Retrieval

1 code implementation11 Sep 2021 Jinpeng Wang, Ziyun Zeng, Bin Chen, Tao Dai, Shu-Tao Xia

The high efficiency in computation and storage makes hashing (including binary hashing and quantization) a common strategy in large-scale retrieval systems.

Contrastive Learning Deep Hashing +1

JSRT: James-Stein Regression Tree

no code implementations18 Oct 2020 Xingchun Xiang, Qingtao Tang, Huaixuan Zhang, Tao Dai, Jiawei Li, Shu-Tao Xia

To address this issue, we propose a novel regression tree, named James-Stein Regression Tree (JSRT) by considering global information from different nodes.

regression

DPAttack: Diffused Patch Attacks against Universal Object Detection

no code implementations16 Oct 2020 Shudeng Wu, Tao Dai, Shu-Tao Xia

Recently, deep neural networks (DNNs) have been widely and successfully used in Object Detection, e. g.

Object object-detection +1

Adversarial Attack on Deep Product Quantization Network for Image Retrieval

no code implementations26 Feb 2020 Yan Feng, Bin Chen, Tao Dai, Shu-Tao Xia

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 especially when dealing with large-scale datasets.

Adversarial Attack Image Retrieval +2

Second-Order Attention Network for Single Image Super-Resolution

1 code implementation CVPR 2019 Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and obtained remarkable performance.

Feature Correlation Image Super-Resolution

Exploiting Common Characters in Chinese and Japanese to Learn Cross-Lingual Word Embeddings via Matrix Factorization

no code implementations WS 2018 Jilei Wang, Shiying Luo, Weiyan Shi, Tao Dai, Shu-Tao Xia

Learning vector space representation of words (i. e., word embeddings) has recently attracted wide research interests, and has been extended to cross-lingual scenario.

Cross-Lingual Word Embeddings Machine Translation +4

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