250 citations · 532 across the 72 of their papers we have counts for
3 papers · 2 filters
LAVA: Label-efficient Visual Learning and Adaptation
Islam Nassar, Munawar Hayat, Ehsan Abbasnejad +3
We present LAVA, a simple yet effective method for multi-domain visual transfer learning with limited data. LAVA builds on a few recent innovations to enable adapting to partially…
EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering
Violetta Shevchenko, Ehsan Abbasnejad, Anthony Dick +2
The availability of clean and diverse labeled data is a major roadblock for training models on complex tasks such as visual question answering (VQA). The extensive work on large vi…
Active Learning by Feature Mixing
Amin Parvaneh, Ehsan Abbasnejad, Damien Teney +3
The promise of active learning (AL) is to reduce labelling costs by selecting the most valuable examples to annotate from a pool of unlabelled data. Identifying these examples is e…