14 citations · 27 across the 13 of their papers we have counts for
6 papers · 1 filter
Sentence-level Prompts Benefit Composed Image Retrieval
Yang Bai, Xinxing Xu, Yong Liu +5
Composed image retrieval (CIR) is the task of retrieving specific images by using a query that involves both a reference image and a relative caption. Most existing CIR models adop…
3D Indoor Instance Segmentation in an Open-World
Mohamed El Amine Boudjoghra, Salwa K. Al Khatib, Jean Lahoud +4
Existing 3D instance segmentation methods typically assume that all semantic classes to be segmented would be available during training and only seen categories are segmented at in…
Towards Instance-adaptive Inference for Federated Learning
Chun-Mei Feng, Kai Yu, Nian Liu +3
Federated learning (FL) is a distributed learning paradigm that enables multiple clients to learn a powerful global model by aggregating local training. However, the performance of…
Diverse Data Augmentation with Diffusions for Effective Test-time Prompt Tuning
Chun-Mei Feng, Kai Yu, Yong Liu +2
Benefiting from prompt tuning, recent years have witnessed the promising performance of pre-trained vision-language models, e.g., CLIP, on versatile downstream tasks. In this paper…
Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment
Sheng Zhang, Muzammal Naseer, Guangyi Chen +4
Large-scale pre-trained Vision Language Models (VLMs) have proven effective for zero-shot classification. Despite the success, most traditional VLMs-based methods are restricted by…
Boosting Adversarial Transferability using Dynamic Cues
Muzammal Naseer, Ahmad Mahmood, Salman Khan +1
The transferability of adversarial perturbations between image models has been extensively studied. In this case, an attack is generated from a known surrogate \eg, the ImageNet tr…