most citedBridging Visual Affective Gap: Borrowing Textual Knowledge by Learning from Noisy Image-Text Pairs

6 citations · 7 across the 5 of their papers we have counts for

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6 papers

cs.CV20256 cited

Bridging Visual Affective Gap: Borrowing Textual Knowledge by Learning from Noisy Image-Text Pairs

Daiqing Wu, Dongbao Yang, Yu Zhou +1

Visual emotion recognition (VER) is a longstanding field that has garnered increasing attention with the advancement of deep neural networks. Although recent studies have achieved…

cs.LG2025

LPCVAE: A Conditional VAE with Long-Term Dependency and Probabilistic Time-Frequency Fusion for Time Series Anomaly Detection

Hanchang Cheng, Weimin Mu, Fan Liu +2

Time series anomaly detection(TSAD) is a critical task in signal processing field, ensuring the reliability of complex systems. Reconstruction-based methods dominate in TSAD. Among…

cs.CL2025

An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability

Daiqing Wu, Dongbao Yang, Sicheng Zhao +2

The advancements in Multimodal Large Language Models (MLLMs) have enabled various multimodal tasks to be addressed under a zero-shot paradigm. This paradigm sidesteps the cost of m…

cs.CV2025

Linguistics-aware Masked Image Modeling for Self-supervised Scene Text Recognition

Yifei Zhang, Chang Liu, Jin Wei +4

Text images are unique in their dual nature, encompassing both visual and linguistic information. The visual component encompasses structural and appearance-based features, while t…

cs.CV20241 cited

Track the Answer: Extending TextVQA from Image to Video with Spatio-Temporal Clues

Yan Zhang, Gangyan Zeng, Huawen Shen +3

Video text-based visual question answering (Video TextVQA) is a practical task that aims to answer questions by jointly reasoning textual and visual information in a given video. I…

cs.CL2024

Falcon-UI: Understanding GUI Before Following User Instructions

Huawen Shen, Chang Liu, Gengluo Li +4

Pursuing human-like interaction for Graphical User Interface (GUI) agents requires understanding the GUI context and following user instructions. However, existing works typically…