4 citations · 7 across the 7 of their papers we have counts for
6 papers · 1 filter
Beyond Saying Less: Fine-Grained Alignment for Informative and Faithful Vision-Language Models
Xingming Long, Jie Zhang, Yuecong Min +2
Object hallucination remains a major challenge for large vision-language models. While off-policy preference optimization proves to be an effective solution, on-policy reinforcemen…
VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task
Xingming Long, Jie Zhang, Shiguang Shan +1
Most research on hallucinations in Large Vision-Language Models (LVLMs) focuses on factual description tasks that prohibit any output absent from the image. However, little attenti…
Semantic or Covariate? A Study on the Intractable Case of Out-of-Distribution Detection
Xingming Long, Jie Zhang, Shiguang Shan +1
The primary goal of out-of-distribution (OOD) detection tasks is to identify inputs with semantic shifts, i.e., if samples from novel classes are absent in the in-distribution (ID)…
Confidence Aware Learning for Reliable Face Anti-spoofing
Xingming Long, Jie Zhang, Shiguang Shan
Current Face Anti-spoofing (FAS) models tend to make overly confident predictions even when encountering unfamiliar scenarios or unknown presentation attacks, which leads to seriou…
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox
Xingming Long, Jie Zhang, Shiguang Shan +1
Most existing out-of-distribution (OOD) detection benchmarks classify samples with novel labels as the OOD data. However, some marginal OOD samples actually have close semantic con…
Generalized Face Liveness Detection via De-fake Face Generator
Xingming Long, Jie Zhang, Shiguang Shan
Previous Face Anti-spoofing (FAS) methods face the challenge of generalizing to unseen domains, mainly because most existing FAS datasets are relatively small and lack data diversi…