Abstract
Fine-grained visual perception enables vision-language models to distinguish subtle attributes and ground their answers in visual evidence. In high-resolution scenes, processing the whole image at greater resolution spends visual tokens on irrelevant content, while isolated crops can lose the context needed to interpret the selected evidence. We introduce EviViT, a lightweight attachment that learns where a pretrained vision transformer should acquire detail. Human visual-search traces supervise a question-conditioned evidence density, which guides regional re-reading from the original pixels and the allocation of visual tokens. A sparse, coordinate-aware bridge then connects the regional features to the global scene, allowing the host to interpret precise evidence in context. Learned with the host backbone frozen, the attachment serves both the base model and compatible post-trained descendants without refitting. Experiments across nine hosts show consistent gains in average fine-grained accuracy. Matched-budget comparisons further show that EviViT outperforms global-only processing at every tested token ceiling while using fewer visual tokens.
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Publication details
- Journal
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- Open access
- Green open access
Cite this article
APA 7
Niu, Y., Chen, Z., Zhang, Y., An, X., Wang, Z., Liao, C. T., Cao, H., & Huang, R. (2026). EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception. https://omanscience.com/en/articles/evivit-evidence-adaptive-vision-transformers-for-fine-grained-perception
MLA 9
Niu, Yaoxin, et al. "EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception." https://omanscience.com/en/articles/evivit-evidence-adaptive-vision-transformers-for-fine-grained-perception.
Chicago (author–date)
Niu, Yaoxin, Zhangquan Chen, Yang Zhang, Xiang An, Zhumei Wang, Chih-Ting Liao, Hongkun Cao, and Ruqi Huang. 2026. "EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception." https://omanscience.com/en/articles/evivit-evidence-adaptive-vision-transformers-for-fine-grained-perception.
Harvard
Niu, Y., Chen, Z., Zhang, Y., An, X., Wang, Z., Liao, C. T., Cao, H. and Huang, R. (2026) 'EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception', Available at: https://omanscience.com/en/articles/evivit-evidence-adaptive-vision-transformers-for-fine-grained-perception.
Vancouver
Niu Y, Chen Z, Zhang Y, An X, Wang Z, Liao CT, et al. EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception. https://omanscience.com/en/articles/evivit-evidence-adaptive-vision-transformers-for-fine-grained-perception
IEEE
Y. Niu, Z. Chen, Y. Zhang, X. An, Z. Wang, C. T. Liao, H. Cao, and R. Huang, "EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception," https://omanscience.com/en/articles/evivit-evidence-adaptive-vision-transformers-for-fine-grained-perception.