Lior Wolf

26.0k citations
208 papers · 14.1k indexed · 6 hit papers · h-index 47

Lior Wolf

196 papers receiving 13.5k citations

Hit Papers

Attend-and...173200520262012201910002.0k3.0k

Peers

Lior Wolf
Comparison fields: 5 of 209
  • Computer Vision and Pattern Recognition 9.9k
  • Signal Processing 2.4k
  • Media Technology 914
  • Artificial Intelligence 3.3k
  • Human-Computer Interaction 363
Replace Honglak Lee with:
Honglak Lee United States
Nanning Zheng China
Hugo Larochelle Canada
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Lior Wolf relative to Honglak Lee United States Honglak Lee's profile →
Citations per field
00.5×3.5×
Honglak Lee · 1×
Citations per year

Countries citing papers authored by Lior Wolf

Since Specialization
Citations

This map shows the geographic impact of Lior Wolf's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lior Wolf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lior Wolf more than expected).

Fields of papers citing papers by Lior Wolf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lior Wolf. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lior Wolf. The network helps show where Lior Wolf may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Lior Wolf, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lior Wolf Line = papers co-authored together Lior Wolf links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20242
2 20242
3 20244
4 20241
5 202415
6 20233
7 202316
8 202216
9
Recovering AES Keys with a Deep Cold Boot Attack
20211
10 202061
11
Audio Denoising with Deep Network Priors.
20194
12 201848
13
Learning to Align the Source Code to the Compiled Object Code
20177
14
Two-Step Disentanglement for Financial Data.
20173
15
In Defense of Product Quantization
20174
16
Temporal Tessellation for Video Annotation and Summarization.
20164
17 2015198
18 2012107
19
Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach
2005137
20
On Projection Matrices and their Applications in Computer Vision.
200114

About Lior Wolf

Lior Wolf is a scholar working on Computer Vision and Pattern Recognition, Space and Planetary Science and Signal Processing, having authored 208 papers that have together received 14.1k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (39 papers), Advanced Vision and Imaging (28 papers), Image Retrieval and Classification Techniques (19 papers), Handwritten Text Recognition Techniques (19 papers), Face and Expression Recognition (18 papers), Generative Adversarial Networks and Image Synthesis (17 papers), Multimodal Machine Learning Applications (16 papers) and Face recognition and analysis (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (9.9k citations), Signal Processing (2.4k citations) and Media Technology (914 citations). Lior Wolf has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Yaniv Taigman, Ming Yang, Marc’Aurelio Ranzato, Tal Hassner, T. Serre, Tomaso Poggio, Stanley Bileschi, Itay Maoz, Daniel Cohen‐Or and Maximilian Riesenhuber. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Graphics Forum, ACM Transactions on Graphics and PLoS Computational Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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