10 accepted papers
Facial expression recognition (FER) in the wild is challenged by co-occurring visual perturbations (e.g., occlusions, pose variations) and label noise. Existing methods often address these issues in isolation, failing to handle their compound effects effectively. To this end, we propose D^3FER (Dual
Multivariate Time Series Forecasting (MTSF) is a critical task in various domains, and Large Language Models (LLMs) for MTSF have recently received considerable attention. Despite significant progress in large-scale time series models, particularly in fine-tuning pre-trained LLMs for MTSF, there are…
This paper tackles the problem of federated domain generalization in person re-identification (FedDG re-ID), aiming to learn a model generalizable to unseen domains with decentralized source domains. Previous methods mainly focus on preventing local overfitting. However, the direction of diversifyin…
The task of multivariate time series (MTS) forecasting has attracted much attention in recent years. However, most existing methods overlook the causal relationship among different variables, which may lead to inaccurate forecasting results. In this paper, we incorporate causality into the forecasti…
With diverse presentation forgery methods emerging continually, detecting the authenticity of images has drawn growing attention. Although existing methods have achieved impressive accuracy in training dataset detection, they still perform poorly in the unseen domain and suffer from forgery of irrel…
Social communication systems must identify toxic voice audio to support moderation that protects the safety and civility of their communities. Toxicity classification for voice depends on both audio style, such as volume and tone, and content, such as the words in the speech individually and in cont…
Music timbre style transfer aims at replacing the instrument timbre in a solo recording with another instrument, while preserving the musical content. Existing GAN-based methods can only achieve timbre style transfer between two given timbres. Inspired by the practice in voice conversion, we propose…
Due to the variety of categories and uneven distribution of available samples, automatic traffic sign detection and recognition is still a challenging task. For those categories with less training data, existing deep learning methods cannot achieve desirable performance, and the overall detection ef…
Text visual question answer (TextVQA) is an important task of visual text understanding, which requires to understand the text generated by text recognition module and provide correct answers to specific questions. Recent works of TextVQA have tried to combine text recognition and multi-modal learni…
Recently, Convolutional Neural Networks (CNN) based image super-resolution (SR) have shown significant success in the literature. However, these methods are implemented as single-path stream to enrich feature maps from the input for the final prediction, which fail to fully incorporate former low-le…