21 citations · 57 across the 8 of their papers we have counts for
19 papers
On the Transferability of Visual Features in Generalized Zero-Shot Learning
Paola Cascante-Bonilla, Leonid Karlinsky, James Seale Smith +2
Generalized Zero-Shot Learning (GZSL) aims to train a classifier that can generalize to unseen classes, using a set of attributes as auxiliary information, and the visual features…
VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models
Felix Vogel, Nina Shvetsova, Leonid Karlinsky +1
Vision-language models trained on large, randomly collected data had significant impact in many areas since they appeared. But as they show great performance in various fields, suc…
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data
Ashraful Islam, Chun-Fu Chen, Rameswar Panda +3
Most existing works in few-shot learning rely on meta-learning the network on a large base dataset which is typically from the same domain as the target dataset. We tackle the prob…
Detector-Free Weakly Supervised Grounding by Separation
Assaf Arbelle, Sivan Doveh, Amit Alfassy +14
Nowadays, there is an abundance of data involving images and surrounding free-form text weakly corresponding to those images. Weakly Supervised phrase-Grounding (WSG) deals with th…
A Broad Study on the Transferability of Visual Representations with Contrastive Learning
Ashraful Islam, Chun-Fu Chen, Rameswar Panda +3
Tremendous progress has been made in visual representation learning, notably with the recent success of self-supervised contrastive learning methods. Supervised contrastive learnin…
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
Yue Meng, Rameswar Panda, Chung-Ching Lin +5
Temporal modelling is the key for efficient video action recognition. While understanding temporal information can improve recognition accuracy for dynamic actions, removing tempor…