78 citations · 245 across the 24 of their papers we have counts for
25 papers
HeuFouFT: Task-Guided Metaheuristic Coordinate Search for Fourier Fine-Tuning
Ruiheng Wang, Yubo Hou, Yakun Zhu +3
We introduce Heuristic-Guided Fourier Fine-Tuning (HeuFouFT), a task-guided framework for selecting trainable frequency coordinates in Fourier fine-tuning. Existing uniform and Gau…
Beyond Sentiment: Structured Information Extraction from Financial News
Daohan Zhu, Sitong Ge, Ruofei Wang +4
Financial sentiment analysis has become a standard component in news-driven stock prediction, yet it reduces rich, multi-dimensional news articles to a single polarity score. We hy…
FlashMem: Distilling Intrinsic Latent Memory via Computation Reuse
Yubo Hou, Zhisheng Chen, Tao Wan +1
The stateless architecture of Large Language Models inherently lacks the mechanism to preserve dynamic context, compelling agents to redundantly reprocess history to maintain long-…
Boosting Semantic Segmentation from the Perspective of Explicit Class Embeddings
Yuhe Liu, Chuanjian Liu, Kai Han +2
Semantic segmentation is a computer vision task that associates a label with each pixel in an image. Modern approaches tend to introduce class embeddings into semantic segmentation…
Sparse Double Descent: Where Network Pruning Aggravates Overfitting
Zheng He, Zeke Xie, Quanzhi Zhu +1
People usually believe that network pruning not only reduces the computational cost of deep networks, but also prevents overfitting by decreasing model capacity. However, our work…
Reasoning with Multi-Structure Commonsense Knowledge in Visual Dialog
Shunyu Zhang, Xiaoze Jiang, Zequn Yang +2
Visual Dialog requires an agent to engage in a conversation with humans grounded in an image. Many studies on Visual Dialog focus on the understanding of the dialog history or the…
KBGN: Knowledge-Bridge Graph Network for Adaptive Vision-Text Reasoning in Visual Dialogue
Xiaoze Jiang, Siyi Du, Zengchang Qin +2
Visual dialogue is a challenging task that needs to extract implicit information from both visual (image) and textual (dialogue history) contexts. Classical approaches pay more att…
DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue
Xiaoze Jiang, Jing Yu, Yajing Sun +4
Visual Dialogue task requires an agent to be engaged in a conversation with human about an image. The ability of generating detailed and non-repetitive responses is crucial for the…
Multi-Level Network for High-Speed Multi-Person Pose Estimation
Ying Huang, Jiankai Zhuang, Zengchang Qin
In multi-person pose estimation, the left/right joint type discrimination is always a hard problem because of the similar appearance. Traditionally, we solve this problem by stacki…
FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition
Ying Huang, Bin Sun, Haipeng Kan +2
Human pose estimation has made significant advancement in recent years. However, the existing datasets are limited in their coverage of pose variety. In this paper, we introduce a…
DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
Xiaoze Jiang, Jing Yu, Zengchang Qin +4
Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue involves multiple questions which cover a broad range of vis…
Structured Knowledge Distillation for Dense Prediction
Yifan Liu, Changyong Shun, Jingdong Wang +1
In this work, we consider transferring the structure information from large networks to compact ones for dense prediction tasks in computer vision. Previous knowledge distillation…
Scene Graph Reasoning with Prior Visual Relationship for Visual Question Answering
Zhuoqian Yang, Zengchang Qin, Jing Yu +1
One of the key issues of Visual Question Answering (VQA) is to reason with semantic clues in the visual content under the guidance of the question, how to model relational semantic…
A sequential guiding network with attention for image captioning
Daouda Sow, Zengchang Qin, Mouhamed Niasse +1
The recent advances of deep learning in both computer vision (CV) and natural language processing (NLP) provide us a new way of understanding semantics, by which we can deal with m…
Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks
Shuangting Liu, Jiaqi Zhang, Yuxin Chen +3
Semantic segmentation is one of the basic topics in computer vision, it aims to assign semantic labels to every pixel of an image. Unbalanced semantic label distribution could have…
Semantic Modeling of Textual Relationships in Cross-Modal Retrieval
Jing Yu, Chenghao Yang, Zengchang Qin +3
Feature modeling of different modalities is a basic problem in current research of cross-modal information retrieval. Existing models typically project texts and images into one em…
Modeling Text with Graph Convolutional Network for Cross-Modal Information Retrieval
Jing Yu, Yuhang Lu, Zengchang Qin +4
Cross-modal information retrieval aims to find heterogeneous data of various modalities from a given query of one modality. The main challenge is to map different modalities into a…
Data Augmentation in Emotion Classification Using Generative Adversarial Networks
Xinyue Zhu, Yifan Liu, Zengchang Qin +1
It is a difficult task to classify images with multiple class labels using only a small number of labeled examples, especially when the label (class) distribution is imbalanced. Em…
Text Generation Based on Generative Adversarial Nets with Latent Variable
Heng Wang, Zengchang Qin, Tao Wan
In this paper, we propose a model using generative adversarial net (GAN) to generate realistic text. Instead of using standard GAN, we combine variational autoencoder (VAE) with ge…
Motif Iteration Model for Network Representation
Lintao Lv, Zengchang Qin, Tao Wan
Social media mining has become one of the most popular research areas in Big Data with the explosion of social networking information from Facebook, Twitter, LinkedIn, Weibo and so…
Logical Parsing from Natural Language Based on a Neural Translation Model
Liang Li, Pengyu Li, Yifan Liu +2
Semantic parsing has emerged as a significant and powerful paradigm for natural language interface and question answering systems. Traditional methods of building a semantic parser…
Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks
Yifan Liu, Zengchang Qin, Zhenbo Luo +1
Recently, realistic image generation using deep neural networks has become a hot topic in machine learning and computer vision. Images can be generated at the pixel level by learni…
Stock Volatility Prediction Using Recurrent Neural Networks with Sentiment Analysis
Yifan Liu, Zengchang Qin, Pengyu Li +1
In this paper, we propose a model to analyze sentiment of online stock forum and use the information to predict the stock volatility in the Chinese market. We have labeled the sent…
Generative Cooperative Net for Image Generation and Data Augmentation
Qiangeng Xu, Zengchang Qin, Tao Wan
How to build a good model for image generation given an abstract concept is a fundamental problem in computer vision. In this paper, we explore a generative model for the task of g…