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20212024
most citedHow Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges

18 citations · 50 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2024

Visual-Augmented Dynamic Semantic Prototype for Generative Zero-Shot Learning

Wenjin Hou, Shiming Chen, Shuhuang Chen +6

Generative Zero-shot learning (ZSL) learns a generator to synthesize visual samples for unseen classes, which is an effective way to advance ZSL. However, existing generative metho…

cs.CV2024

Cross-Modal Self-Training: Aligning Images and Pointclouds to Learn Classification without Labels

Amaya Dharmasiri, Muzammal Naseer, Salman Khan +1

Large-scale vision 2D vision language models, such as CLIP can be aligned with a 3D encoder to learn generalizable (open-vocabulary) 3D vision models. However, current methods requ…

cs.CV2024

Language Guided Domain Generalized Medical Image Segmentation

Shahina Kunhimon, Muzammal Naseer, Salman Khan +1

Single source domain generalization (SDG) holds promise for more reliable and consistent image segmentation across real-world clinical settings particularly in the medical domain,…

cs.CV2024

ELGC-Net: Efficient Local-Global Context Aggregation for Remote Sensing Change Detection

Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal +2

Deep learning has shown remarkable success in remote sensing change detection (CD), aiming to identify semantic change regions between co-registered satellite image pairs acquired…

cs.CV20249 cited

AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation

Yuning Cui, Syed Waqas Zamir, Salman Khan +3

In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent lim…

cs.CV20242 cited

Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery

Mubashir Noman, Muzammal Naseer, Hisham Cholakkal +3

Recent advances in unsupervised learning have demonstrated the ability of large vision models to achieve promising results on downstream tasks by pre-training on large amount of un…