ICCV Poster "vision transformers" Papers

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LeGrad: An Explainability Method for Vision Transformers via Feature Formation Sensitivity

Walid Bousselham, Angie Boggust, Sofian Chaybouti et al.

ICCV 2025posterarXiv:2404.03214
24
citations

Semantic Alignment and Reinforcement for Data-Free Quantization of Vision Transformers

Yunshan Zhong, Yuyao Zhou, Yuxin Zhang et al.

ICCV 2025posterarXiv:2412.16553

Variance-Based Pruning for Accelerating and Compressing Trained Networks

Uranik Berisha, Jens Mehnert, Alexandru Condurache

ICCV 2025posterarXiv:2507.12988
1
citations

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers

Hanwen Cao, Haobo Lu, Xiaosen Wang et al.

ICCV 2025posterarXiv:2508.12384
1
citations

ViT-Linearizer: Distilling Quadratic Knowledge into Linear-Time Vision Models

Guoyizhe Wei, Rama Chellappa

ICCV 2025posterarXiv:2504.00037
2
citations

VSSD: Vision Mamba with Non-Causal State Space Duality

Yuheng Shi, Mingjia Li, Minjing Dong et al.

ICCV 2025posterarXiv:2407.18559
24
citations