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20212026
most citedMulti-class Token Transformer for Weakly Supervised Semantic Segmentation

19 citations · 40 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

MicroSDF: Microfacet-Driven Hybrid Neural SDFs for Mixed-Reflectance Surface Reconstruction

Lejia Ye, Yuhua Xu, Yulan Guo +2

Accurate 3D reconstruction in real-world environments remains a significant challenge due to the coexistence of reflective and non-reflective surfaces, which pose distinct modeling…

cs.CV2026

Warp-free Cross-view Geo-localization via Feature-space Consensus Mining

Zhuo Song, Lian Xu, Runqing Jiang +4

Cross-view geo-localization is challenging due to drastic viewpoint changes and large appearance discrepancies between street-level and satellite imagery. Although existing methods…

cs.CV2026

Learning Structured Visual Compositional Representations for Weakly Supervised Referring Expression Comprehension

Lian Xu, Mohammed Bennamoun, Farid Boussaid +3

Referring expression comprehension (REC) aims to localize the object in an image described by natural language. In Weakly supervised REC (WREC), existing approaches primarily opera…

cs.CV2026

ScalePredictor: Instance-aware Scale Learning for Accurate Quantization of Vision Transformers

Changjun Li, Runqing Jiang, Lian Xu +3

Vision Transformers have achieved remarkable success in many fields, yet their deployment on edge devices remains challenging due to their substantial computational demands. Post-T…

cs.CV2026

Dual Distribution Estimation for Zero-shot Noisy Test-Time Adaptation with VLMs

Wenjie Zhu, Yabin Zhang, Liang Xu +3

While test-time adaptation (TTA) empowers vision-language models to adapt without costly retraining, it remains highly vulnerable to out-of-distribution (OOD) outliers prevalent in…

cs.CV2026

Fact or Fake? Assessing the Role of Deepfake Detectors in Multimodal Misinformation Detection

A S M Sharifuzzaman Sagar, Mohammed Bennamoun, Farid Boussaid +4

In multimodal misinformation, deception usually arises not just from pixel-level manipulations in an image, but from the semantic and contextual claim jointly expressed by the imag…