6 papers · 1 filter
Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study
Hao Dong, Hongzhao Li, Shupan Li +3
Despite the growing popularity of Multimodal Domain Generalization (MMDG) for enhancing model robustness, it remains unclear whether reported performance gains reflect genuine algo…
Towards Multimodal Domain Generalization with Few Labels
Hongzhao Li, Hao Dong, Hualei Wan +3
Multimodal models ideally should generalize to unseen domains while remaining data-efficient to reduce annotation costs. To this end, we introduce and study a new problem, Semi-Sup…
Compositional Zero-Shot Learning: A Survey
Ans Munir, Faisal Z. Qureshi, Mohsen Ali +1
Compositional Zero-Shot Learning (CZSL) is a critical task in computer vision that enables models to recognize unseen combinations of known attributes and objects during inference,…
TLAC: Two-stage LMM Augmented CLIP for Zero-Shot Classification
Ans Munir, Faisal Z. Qureshi, Muhammad Haris Khan +1
Contrastive Language-Image Pretraining (CLIP) has shown impressive zero-shot performance on image classification. However, state-of-the-art methods often rely on fine-tuning techni…
Attention Based Simple Primitives for Open World Compositional Zero-Shot Learning
Ans Munir, Faisal Z. Qureshi, Muhammad Haris Khan +1
Compositional Zero-Shot Learning (CZSL) aims to predict unknown compositions made up of attribute and object pairs. Predicting compositions unseen during training is a challenging…
Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment
Muhammad Sohail Danish, Muhammad Haris Khan, Muhammad Akhtar Munir +2
In this work, we tackle the problem of domain generalization for object detection, specifically focusing on the scenario where only a single source domain is available. We propose…