← Search

lixiong Qin

7 accepted papers

2025

Face-Human-Bench: A Comprehensive Benchmark of Face and Human Understanding for Multi-modal Assistants

NeurIPS 2025poster

Faces and humans are crucial elements in social interaction and are widely included in everyday photos and videos. Therefore, a deep understanding of faces and humans will enable multi-modal assistants to achieve improved response quality and broadened application scope. Currently, the multi-modal a…

Cited by 0SourcecodeScholar
2025

Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal

AAAI 2025technical

Incomplete multi-view multi-label classification aims to accurately predict labels for each sample in the face of some missing views. Due to its widespread presence in real-world scenarios, it has become an extensively researched topic. In addition to the challenges brought by missing views, it also…

Cited by 0SourcePDFScholar
2025

VA-AR: Learning Velocity-Aware Action Representations with Mixture of Window Attention

AAAI 2025technical

Action recognition is a crucial task in artificial intelligence, with significant implications across various domains. We initially perform a comprehensive analysis of seven prominent action recognition methods across five widely-used datasets. This analysis reveals a critical, yet previously overlo…

2024

Open-Set Facial Expression Recognition

AAAI 2024technical

Facial expression recognition (FER) models are typically trained on datasets with a fixed number of seven basic classes. However, recent research works (Cowen et al. 2021; Bryant et al. 2022; Kollias 2023) point out that there are far more expressions than the basic ones. Thus, when these models are…

Cited by 4SourcePDFScholar
2023

Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation

ICCV 2023poster

Deep neural networks are vulnerable to universal adversarial perturbation (UAP), an instance-agnostic perturbation capable of fooling the target model for most samples. Compared to instance-specific adversarial examples, UAP is more challenging as it needs to generalize across various samples and mo…

Cited by 30PDFcodeScholar
2023

Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognition

NeurIPS 2023poster

Facial expression data is characterized by a significant imbalance, with most collected data showing happy or neutral expressions and fewer instances of fear or disgust. This imbalance poses challenges to facial expression recognition (FER) models, hindering their ability to fully understand various…

Cited by 24SourcePDFScholar