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20242026
most cited: Bimodal Online Test-Time Adaptation for CLIP

1 citations · 1 across the 5 of their papers we have counts for

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cs.CV2026

PIVM: Diffusion-Based Prior-Integrated Variation Modeling for Anatomically Precise Abdominal CT Synthesis

Dinglun He, Baoming Zhang, Xu Wang +3

Abdominal CT data are limited by high annotation costs and privacy constraints, which hinder the development of robust segmentation and diagnostic models. We present a Prior-Integr…

cs.CV2026

Learnability-Driven Submodular Optimization for Active Roadside 3D Detection

Ruiyu Mao, Baoming Zhang, Nicholas Ruozzi +1

Roadside perception datasets are typically constructed via cooperative labeling between synchronized vehicle and roadside frame pairs. However, real deployment often requires annot…

cs.CV2025

SafeFix: Targeted Model Repair via Controlled Image Generation

Ouyang Xu, Baoming Zhang, Ruiyu Mao +1

Deep learning models for visual recognition often exhibit systematic errors due to underrepresented semantic subpopulations. Although existing debugging frameworks can pinpoint the…

cs.CV20241 cited

: Bimodal Online Test-Time Adaptation for CLIP

Sarthak Kumar Maharana, Baoming Zhang, Leonid Karlinsky +2

Although open-vocabulary classification models like Contrastive Language Image Pretraining (CLIP) have demonstrated strong zero-shot learning capabilities, their robustness to comm…

cs.CV2024

PALM: Pushing Adaptive Learning Rate Mechanisms for Continual Test-Time Adaptation

Sarthak Kumar Maharana, Baoming Zhang, Yunhui Guo

Real-world vision models in dynamic environments face rapid shifts in domain distributions, leading to decreased recognition performance. Using unlabeled test data, continuous test…