no code implementations • 3 Dec 2024 • Yiftach Edelstein, Or Patashnik, Dana Cohen-Bar, Lihi Zelnik-Manor
In this work, we bridge the quality gap between methods that directly generate 3D representations and ones that reconstruct 3D objects from multi-view images.
1 code implementation • 7 Sep 2024 • Tom Bekor, Niv Nayman, Lihi Zelnik-Manor
Data augmentation has become an integral part of deep learning, as it is known to improve the generalization capabilities of neural networks.
no code implementations • 13 Mar 2024 • Anton Agafonov, Lihi Zelnik-Manor
Our experiment shows that our method achieves plausible deformation of the soft tissue layer, even for unseen scenarios.
no code implementations • 19 Apr 2022 • Niv Nayman, Avram Golbert, Asaf Noy, Tan Ping, Lihi Zelnik-Manor
Encouraged by the recent transferability results of self-supervised models, we propose a method that combines self-supervised and supervised pretraining to generate models with both high diversity and high accuracy, and as a result high transferability.
1 code implementation • 24 Oct 2021 • Niv Nayman, Yonathan Aflalo, Asaf Noy, Rong Jin, Lihi Zelnik-Manor
Practical use of neural networks often involves requirements on latency, energy and memory among others.
1 code implementation • CVPR 2022 • Emanuel Ben-Baruch, Tal Ridnik, Itamar Friedman, Avi Ben-Cohen, Nadav Zamir, Asaf Noy, Lihi Zelnik-Manor
We propose to estimate the class distribution using a dedicated temporary model, and we show its improved efficiency over a naive estimation computed using the dataset's partial annotations.
Ranked #1 on
Multi-Label Classification
on OpenImages-v6
1 code implementation • 26 Sep 2021 • Tamar Glaser, Emanuel Ben-Baruch, Gilad Sharir, Nadav Zamir, Asaf Noy, Lihi Zelnik-Manor
We address this gap with a tailor-made solution, combining the power of CNNs for image representation and transformers for album representation to perform global reasoning on image collection, offering a practical and efficient solution for photo albums event recognition.
1 code implementation • ICCV 2021 • Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Baruch, Itamar Friedman, Lihi Zelnik-Manor
We argue that using a single embedding vector to represent an image, as commonly practiced, is not sufficient to rank both relevant seen and unseen labels accurately.
Ranked #3 on
Multi-label zero-shot learning
on Open Images V4
5 code implementations • 22 Apr 2021 • Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelnik-Manor
ImageNet-1K serves as the primary dataset for pretraining deep learning models for computer vision tasks.
Ranked #2 on
Image Classification
on Stanford Cars
2 code implementations • 25 Mar 2021 • Gilad Sharir, Asaf Noy, Lihi Zelnik-Manor
Methods that reach State of the Art (SotA) accuracy, usually make use of 3D convolution layers as a way to abstract the temporal information from video frames.
Ranked #25 on
Action Recognition
on UCF101
(using extra training data)
2 code implementations • 23 Feb 2021 • Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik-Manor
Realistic use of neural networks often requires adhering to multiple constraints on latency, energy and memory among others.
Ranked #21 on
Neural Architecture Search
on ImageNet
no code implementations • 12 Jan 2021 • Asaf Noy, Yi Xu, Yonathan Aflalo, Lihi Zelnik-Manor, Rong Jin
We show that convergence to a global minimum is guaranteed for networks with widths quadratic in the sample size and linear in their depth at a time logarithmic in both.
5 code implementations • ICCV 2021 • Emanuel Ben-Baruch, Tal Ridnik, Nadav Zamir, Asaf Noy, Itamar Friedman, Matan Protter, Lihi Zelnik-Manor
In this paper, we introduce a novel asymmetric loss ("ASL"), which operates differently on positive and negative samples.
Ranked #4 on
Multi-Label Classification
on NUS-WIDE
1 code implementation • CVPR 2020 • Amir Markovitz, Gilad Sharir, Itamar Friedman, Lihi Zelnik-Manor, Shai Avidan
We propose a new method for anomaly detection of human actions.
Ranked #7 on
Video Anomaly Detection
on HR-UBnormal
no code implementations • 15 Oct 2019 • Hussam Lawen, Avi Ben-Cohen, Matan Protter, Itamar Friedman, Lihi Zelnik-Manor
Furthermore, we show the representation power of our ReID network via SotA results on a different task of multi-object tracking.
Ranked #18 on
Person Re-Identification
on Market-1501
2 code implementations • NeurIPS 2019 • Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik-Manor
This paper introduces a novel optimization method for differential neural architecture search, based on the theory of prediction with expert advice.
1 code implementation • 8 Apr 2019 • Asaf Noy, Niv Nayman, Tal Ridnik, Nadav Zamir, Sivan Doveh, Itamar Friedman, Raja Giryes, Lihi Zelnik-Manor
In this paper, we propose a differentiable search space that allows the annealing of architecture weights, while gradually pruning inferior operations.
no code implementations • 31 Jan 2019 • Shay Perera, Ayellet Tal, Lihi Zelnik-Manor
This paper deals with the prediction of the memorability of a given image.
1 code implementation • ICCV 2019 • Alon Shoshan, Roey Mechrez, Lihi Zelnik-Manor
Our approach considers an "objective-space" as the space of all linear combinations of two objectives, and the Dynamic-Net is emulating the traversing of this objective-space at test-time, without any further training.
1 code implementation • ICCV 2019 • Firas Shama, Roey Mechrez, Alon Shoshan, Lihi Zelnik-Manor
In this paper we propose a novel method that makes an explicit use of the discriminator in test-time, in a feedback manner in order to improve the generator results.
8 code implementations • 20 Sep 2018 • Yochai Blau, Roey Mechrez, Radu Timofte, Tomer Michaeli, Lihi Zelnik-Manor
This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECCV 2018.
Ranked #33 on
Video Quality Assessment
on MSU SR-QA Dataset
no code implementations • CVPR 2018 • Tal Tlusty, Tomer Michaeli, Tali Dekel, Lihi Zelnik-Manor
We present an algorithm for modifying small non-local variations between repeating structures and patterns in multiple images of the same scene.
3 code implementations • 13 Mar 2018 • Roey Mechrez, Itamar Talmi, Firas Shama, Lihi Zelnik-Manor
Maintaining natural image statistics is a crucial factor in restoration and generation of realistic looking images.
3 code implementations • ECCV 2018 • Roey Mechrez, Itamar Talmi, Lihi Zelnik-Manor
Feed-forward CNNs trained for image transformation problems rely on loss functions that measure the similarity between the generated image and a target image.
1 code implementation • 28 Sep 2017 • Roey Mechrez, Eli Shechtman, Lihi Zelnik-Manor
Recent work has shown impressive success in transferring painterly style to images.
1 code implementation • 7 Dec 2016 • Roey Mechrez, Eli Shechtman, Lihi Zelnik-Manor
Have you ever taken a picture only to find out that an unimportant background object ended up being overly salient?
1 code implementation • CVPR 2017 • Itamar Talmi, Roey Mechrez, Lihi Zelnik-Manor
We propose a novel measure for template matching named Deformable Diversity Similarity -- based on the diversity of feature matches between a target image window and the template.
no code implementations • ICCV 2015 • Daniel Glasner, Pascal Fua, Todd Zickler, Lihi Zelnik-Manor
In this paper we explore interactions between the appearance of an outdoor scene and the ambient temperature.
no code implementations • CVPR 2015 • Nir Ben-Zrihem, Lihi Zelnik-Manor
We introduce RIANN (Ring Intersection Approximate Nearest Neighbor search), an algorithm for matching patches of a video to a set of reference patches in real-time.
no code implementations • CVPR 2014 • Ran Margolin, Lihi Zelnik-Manor, Ayellet Tal
In this paper, we show that the most commonly-used measures for evaluating both non-binary maps and binary maps do not always provide a reliable evaluation.
no code implementations • CVPR 2013 • Ran Margolin, Ayellet Tal, Lihi Zelnik-Manor
Our key contribution is a novel and fast approach to compute pattern distinctness.
no code implementations • CVPR 2013 • Dmitry Rudoy, Dan B. Goldman, Eli Shechtman, Lihi Zelnik-Manor
For example, the time each video frame is observed is a fraction of a second, while a still image can be viewed leisurely.
1 code implementation • 16 Apr 2012 • Dmitry Rudoy, Dan B. Goldman, Eli Shechtman, Lihi Zelnik-Manor
In this work we propose a crowdsourced method for acquisition of gaze direction data from a virtually unlimited number of participants, using a robust self-reporting mechanism (see Figure 1).
Social and Information Networks Human-Computer Interaction