25 citations · 87 across the 56 of their papers we have counts for
7 papers · 1 filter
SpatialBench: Is Your Spatial Foundation Model an All-Round Player?
Haosong Peng, Hao Li, Jiaqi Chen +10
While spatial foundation models have demonstrated impressive performance on standard datasets, a critical question remains: are they truly all-round players capable of generalizing…
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
Fushuo Huo, Wenchao Xu, Zhong Zhang +3
While Large Vision-Language Models (LVLMs) have rapidly advanced in recent years, the prevalent issue known as the `hallucination' problem has emerged as a significant bottleneck,…
Detached and Interactive Multimodal Learning
Yunfeng Fan, Wenchao Xu, Haozhao Wang +2
Recently, Multimodal Learning (MML) has gained significant interest as it compensates for single-modality limitations through comprehensive complementary information within multimo…
Dual Expert Distillation Network for Generalized Zero-Shot Learning
Zhijie Rao, Jingcai Guo, Xiaocheng Lu +5
Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping…
Non-Exemplar Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement
Fushuo Huo, Wenchao Xu, Jingcai Guo +3
This paper investigates a new, practical, but challenging problem named Non-exemplar Online Class-incremental continual Learning (NO-CL), which aims to preserve the discernibility…
ProCC: Progressive Cross-primitive Compatibility for Open-World Compositional Zero-Shot Learning
Fushuo Huo, Wenchao Xu, Song Guo +4
Open-World Compositional Zero-shot Learning (OW-CZSL) aims to recognize novel compositions of state and object primitives in images with no priors on the compositional space, which…
SNEAK: Synonymous Sentences-Aware Adversarial Attack on Natural Language Video Localization
Wenbo Gou, Wen Shi, Jian Lou +3
Natural language video localization (NLVL) is an important task in the vision-language understanding area, which calls for an in-depth understanding of not only computer vision and…