activity
20182024
most citedDelta-encoder: an effective sample synthesis method for few-shot object recognition

289 citations · 554 across the 28 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021★ 4 cited

Unsupervised Domain Generalization by Learning a Bridge Across Domains

Sivan Harary, Eli Schwartz, Assaf Arbelle +11

The ability to generalize learned representations across significantly different visual domains, such as between real photos, clipart, paintings, and sketches, is a fundamental cap…

cs.CV2021

CHARTER: heatmap-based multi-type chart data extraction

Joseph Shtok, Sivan Harary, Ophir Azulai +3

The digital conversion of information stored in documents is a great source of knowledge. In contrast to the documents text, the conversion of the embedded documents graphics, such…

cs.CV2021★ 10 cited

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…

cs.CV2021

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…

cs.CV2021★ 1 cited

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…

cs.CV2021★ 21 cited

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…