b'Lingqiao Liu'

research

∙ 08/22/2023

Domain Generalization via Rationale Invariance

This paper offers a new perspective to ease the challenge of domain gene...

0 Liang Chen, et al. ∙

research

∙ 06/28/2023

You Can Generate It Again: Data-to-text Generation with Verification and Correction Prompting

Despite significant advancements in existing models, generating text des...

0 Xuan Ren, et al. ∙

research

∙ 05/29/2023

Learning Conditional Attributes for Compositional Zero-Shot Learning

Compositional Zero-Shot Learning (CZSL) aims to train models to recogniz...

0 Qingsheng Wang, et al. ∙

research

∙ 05/23/2023

Out-of-Distribution Generalization in Text Classification: Past, Present, and Future

Machine learning (ML) systems in natural language processing (NLP) face ...

0 Linyi Yang, et al. ∙

research

∙ 05/22/2023

The CLIP Model is Secretly an Image-to-Prompt Converter

The Stable Diffusion model is a prominent text-to-image generation model...

0 Yuxuan Ding, et al. ∙

research

∙ 04/10/2023

Improved Test-Time Adaptation for Domain Generalization

The main challenge in domain generalization (DG) is to handle the distri...

0 Liang Chen, et al. ∙

research

∙ 03/17/2023

Revisiting Image Reconstruction for Semi-supervised Semantic Segmentation

Autoencoding, which aims to reconstruct the input images through a bottl...

0 Yuhao Lin, et al. ∙

research

∙ 03/03/2023

Learning Common Rationale to Improve Self-Supervised Representation for Fine-Grained Visual Recognition Problems

Self-supervised learning (SSL) strategies have demonstrated remarkable p...

30 Yangyang Shu, et al. ∙

research

∙ 12/05/2022

Generalizable Person Re-Identification via Viewpoint Alignment and Fusion

In the current person Re-identification (ReID) methods, most domain gene...

0 Bingliang Jiao, et al. ∙

research

∙ 10/10/2022

Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization

Semi-supervised semantic segmentation requires the model to effectively ...

0 Hai-Ming Xu, et al. ∙

research

∙ 09/29/2022

Regularizing Neural Network Training via Identity-wise Discriminative Feature Suppression

It is well-known that a deep neural network has a strong fitting capabil...

0 Avraham Chapman, et al. ∙

research

∙ 08/20/2022

Pretrained Language Encoders are Natural Tagging Frameworks for Aspect Sentiment Triplet Extraction

Aspect Sentiment Triplet Extraction (ASTE) aims to extract the spans of ...

0 Yanjie Gou, et al. ∙

research

∙ 08/18/2022

Single-Stage Open-world Instance Segmentation with Cross-task Consistency Regularization

Open-world instance segmentation (OWIS) aims to segment class-agnostic i...

8 Xizhe Xue, et al. ∙

research

∙ 08/01/2022

Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism

The challenge of fine-grained visual recognition often lies in discoveri...

0 Yangyang Shu, et al. ∙

research

∙ 07/19/2022

Don't Stop Learning: Towards Continual Learning for the CLIP Model

The Contrastive Language-Image Pre-training (CLIP) Model is a recently p...

0 Yuxuan Ding, et al. ∙

research

∙ 07/06/2022

Two-stage Decision Improves Open-Set Panoptic Segmentation

Open-set panoptic segmentation (OPS) problem is a new research direction...

0 Hai-Ming Xu, et al. ∙

research

∙ 03/23/2022

Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection

Recent studies in deepfake detection have yielded promising results when...

0 Liang Chen, et al. ∙

research

∙ 01/06/2022

Multi-Domain Joint Training for Person Re-Identification

Deep learning-based person Re-IDentification (ReID) often requires a lar...

0 Lu Yang, et al. ∙

research

∙ 08/05/2021

Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentation

Semantic segmentation is a crucial image understanding task, where each ...

2 Duo Peng, et al. ∙

research

∙ 05/22/2021

Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection

Weakly-supervised anomaly detection aims at learning an anomaly detector...

0 Yingjie Zhou, et al. ∙

research

∙ 04/30/2021

Center Prediction Loss for Re-identification

The training loss function that enforces certain training sample distrib...

0 Lu Yang, et al. ∙

research

∙ 03/09/2021

Pluggable Weakly-Supervised Cross-View Learning for Accurate Vehicle Re-Identification

Learning cross-view consistent feature representation is the key for acc...

0 Lu Yang, et al. ∙

research

∙ 10/26/2020

Where to Look and How to Describe: Fashion Image Retrieval with an Attentional Heterogeneous Bilinear Network

Fashion products typically feature in compositions of a variety of style...

0 Haibo Su, et al. ∙

research

∙ 10/12/2020

Dynamic Memory Enhanced Transformer for End-to-end Task-Oriented Dialogue System

Recent studies try to build task-oriented dialogue system in an end-to-e...

0 Yanjie Gou, et al. ∙

research

∙ 07/07/2020

Semi-Supervised Crowd Counting via Self-Training on Surrogate Tasks

Most existing crowd counting systems rely on the availability of the obj...

7 Yan Liu, et al. ∙

research

∙ 02/29/2020

Towards Using Count-level Weak Supervision for Crowd Counting

Most existing crowd counting methods require object location-level annot...

0 Yinjie Lei, et al. ∙

research

∙ 02/11/2020

Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning

Hyperspectral image(HSI) classification has been improved with convoluti...

0 Haokui Zhang, et al. ∙

research

∙ 01/09/2020

Semi-supervised Learning via Conditional Rotation Angle Estimation

Self-supervised learning (SlfSL), aiming at learning feature representat...

38 Hai-Ming Xu, et al. ∙

research

∙ 12/10/2019

To Balance or Not to Balance: An Embarrassingly Simple Approach for Learning with Long-Tailed Distributions

Real-world visual data often exhibits a long-tailed distribution, where ...

0 Junjie Zhang, et al. ∙

research

∙ 11/15/2019

DNNRE: A Dynamic Neural Network for Distant Supervised Relation Extraction

Distant Supervised Relation Extraction (DSRE) is usually formulated as a...

0 Yanjie Gou, et al. ∙

research

∙ 11/12/2019

Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction

Charge prediction, determining charges for criminal cases by analyzing t...

0 Liangyi Kang, et al. ∙

research

∙ 09/28/2019

Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation

This paper tackles the problem of video object segmentation. We are spec...

29 Yu Liu, et al. ∙

research

∙ 09/22/2019

Structured Binary Neural Networks for Image Recognition

We propose methods to train convolutional neural networks (CNNs) with bo...

0 Bohan Zhuang, et al. ∙

research

∙ 08/19/2019

In defense of OSVOS

As a milestone for video object segmentation, one-shot video object segm...

7 Yu Liu, et al. ∙

research

∙ 08/10/2019

Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations

This paper tackles the problem of training a deep convolutional neural n...

0 Bohan Zhuang, et al. ∙

research

∙ 07/29/2019

V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices

One of the primary challenges faced by deep learning is the degree to wh...

2 Damien Teney, et al. ∙

research

∙ 04/04/2019

Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection

Deep autoencoder has been extensively used for anomaly detection. Traini...

34 Dong Gong, et al. ∙

research

∙ 03/27/2019

Training Quantized Network with Auxiliary Gradient Module

In this paper, we seek to tackle two challenges in training low-precisio...

0 Bohan Zhuang, et al. ∙

research

∙ 03/01/2019

A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning

One key issue in managing a large scale 3D shape dataset is to identify ...

0 Yinjie Lei, et al. ∙

research

∙ 01/22/2019

RPC: A Large-Scale Retail Product Checkout Dataset

Over recent years, emerging interest has occurred in integrating compute...

0 Xiu-Shen Wei, et al. ∙

research

∙ 01/12/2019

Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes

As the post-processing step for object detection, non-maximum suppressio...

12 Yu Liu, et al. ∙

research

∙ 12/11/2018

Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification

Vehicle re-identification is an important problem and becomes desirable ...

10 Xiu-Shen Wei, et al. ∙

research

∙ 11/22/2018

Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation

In this paper, we propose to train convolutional neural networks (CNNs) ...

0 Bohan Zhuang, et al. ∙

research

∙ 11/22/2018

Rethinking Binary Neural Network for Accurate Image Classification and Semantic Segmentation

In this paper, we propose to train a network with both binary weights an...

0 Bohan Zhuang, et al. ∙

research

∙ 08/30/2018

Towards Effective Deep Embedding for Zero-Shot Learning

Zero-shot learning (ZSL) attempts to recognize visual samples of unseen ...

0 Lei Zhang, et al. ∙

research

∙ 06/05/2018

Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

Deep neural networks have achieved remarkable success in single image su...

4 Lei Zhang, et al. ∙

research

∙ 05/11/2018

Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples

Humans are capable of learning a new fine-grained concept with very litt...

0 Xiu-Shen Wei, et al. ∙

research

∙ 11/01/2017

Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization

Landmark/pose estimation in single monocular images have received much e...

0 Yu Chen, et al. ∙

research

∙ 11/01/2017

Towards Effective Low-bitwidth Convolutional Neural Networks

This paper tackles the problem of training a deep convolutional neural n...

0 Bohan Zhuang, et al. ∙

research

∙ 07/18/2017

Visually Aligned Word Embeddings for Improving Zero-shot Learning

Zero-shot learning (ZSL) highly depends on a good semantic embedding to ...

0 Ruizhi Qiao, et al. ∙

Lingqiao Liu

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