4 citations · 5 across the 10 of their papers we have counts for
8 papers · 1 filter
StepAL: Step-aware Active Learning for Cataract Surgical Videos
Nisarg A. Shah, Bardia Safaei, Shameema Sikder +2
Active learning (AL) can reduce annotation costs in surgical video analysis while maintaining model performance. However, traditional AL methods, developed for images or short vide…
Certainty and Uncertainty Guided Active Domain Adaptation
Bardia Safaei, Vibashan VS, Vishal M. Patel
Active Domain Adaptation (ADA) adapts models to target domains by selectively labeling a few target samples. Existing ADA methods prioritize uncertain samples but overlook confiden…
Filter Images First, Generate Instructions Later: Pre-Instruction Data Selection for Visual Instruction Tuning
Bardia Safaei, Faizan Siddiqui, Jiacong Xu +2
Visual instruction tuning (VIT) for large vision-language models (LVLMs) requires training on expansive datasets of image-instruction pairs, which can be costly. Recent efforts in…
Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models
Jiacong Xu, Shao-Yuan Lo, Bardia Safaei +2
Zero-Shot Anomaly Detection (ZSAD) is an emerging AD paradigm. Unlike the traditional unsupervised AD setting that requires a large number of normal samples to train a model, ZSAD…
Active Learning for Vision-Language Models
Bardia Safaei, Vishal M. Patel
Pre-trained vision-language models (VLMs) like CLIP have demonstrated impressive zero-shot performance on a wide range of downstream computer vision tasks. However, there still exi…
Gradient-Regularized Out-of-Distribution Detection
Sina Sharifi, Taha Entesari, Bardia Safaei +2
One of the challenges for neural networks in real-life applications is the overconfident errors these models make when the data is not from the original training distribution. Addr…
Entropic Open-set Active Learning
Bardia Safaei, Vibashan VS, Celso M. de Melo +1
Active Learning (AL) aims to enhance the performance of deep models by selecting the most informative samples for annotation from a pool of unlabeled data. Despite impressive perfo…
Open-Set Automatic Target Recognition
Bardia Safaei, Vibashan VS, Celso M. de Melo +2
Automatic Target Recognition (ATR) is a category of computer vision algorithms which attempts to recognize targets on data obtained from different sensors. ATR algorithms are exten…