73 citations · 414 across the 36 of their papers we have counts for
6 papers · 1 filter
Balancing Specialization, Generalization, and Compression for Detection and Tracking
Dotan Kaufman, Koby Bibas, Eran Borenstein +2
We propose a method for specializing deep detectors and trackers to restricted settings. Our approach is designed with the following goals in mind: (a) Improving accuracy in restri…
Transferability and Hardness of Supervised Classification Tasks
Anh T. Tran, Cuong V. Nguyen, Tal Hassner
We propose a novel approach for estimating the difficulty and transferability of supervised classification tasks. Unlike previous work, our approach is solution agnostic and does n…
FSGAN: Subject Agnostic Face Swapping and Reenactment
Yuval Nirkin, Yosi Keller, Tal Hassner
We present Face Swapping GAN (FSGAN) for face swapping and reenactment. Unlike previous work, FSGAN is subject agnostic and can be applied to pairs of faces without requiring train…
Toward Understanding Catastrophic Forgetting in Continual Learning
Cuong V. Nguyen, Alessandro Achille, Michael Lam +3
We study the relationship between catastrophic forgetting and properties of task sequences. In particular, given a sequence of tasks, we would like to understand which properties o…
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation
Matan Goldman, Tal Hassner, Shai Avidan
The field of self-supervised monocular depth estimation has seen huge advancements in recent years. Most methods assume stereo data is available during training but usually under-u…
Precise Detection in Densely Packed Scenes
Eran Goldman, Roei Herzig, Aviv Eisenschtat +4
Man-made scenes can be densely packed, containing numerous objects, often identical, positioned in close proximity. We show that precise object detection in such scenes remains a c…