Yoad Tewel

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I am a Computer Science PhD candidate at Tel-Aviv University, working in the Deep Learning Lab under the supervision of Prof. Lior Wolf, and a research intern at NVIDIA Research, working with Gal Chechik, Rinon Gal and Yuval Atzmon.

My research focuses on the intersection of computer vision, natural language processing, and machine learning. In particular, I am exploring ways to leverage text-and-image foundation models for solving zero-shot tasks.

Publications

2024

  1. Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models
    Yoad Tewel, Rinon Gal, Dvir Samuel, Yuval Atzmon, Lior Wolf, and Gal Chechik
    paper page Code
  2. Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models
    Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, and Rami Ben-Ari
    paper Code
  3. Make It Count: Text-to-Image Generation with an Accurate Number of Objects
    Lital Binyamin, Yoad Tewel, Hilit Segev, Eran Hirsch, Royi Rassin, and Gal Chechik
    paper page Code
  4. Training-Free Consistent Text-to-Image Generation
    Yoad Tewel, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, and Yuval Atzmon
    SIGGRAPH, 2024
    paper page Code

2023

  1. Key-Locked Rank One Editing for Text-to-Image Personalization
    Yoad Tewel, Rinon Gal, Gal Chechik, and Yuval Atzmon
    SIGGRAPH, 2023
    paper page
  2. Zero-Shot Video Captioning with Evolving Pseudo-Tokens
    Yoad Tewel, Yoav Shalev, Roy Nadler, Idan Schwartz, and Lior Wolf
    BMVC, 2023 (Oral)
    paper Code

2022

  1. What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs
    Tal Shaharabany, Yoad Tewel, and Lior Wolf
    NeurIPS, 2022
    paper Code
  2. ZeroCap: Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic
    Yoad Tewel, Yoav Shalev, Idan Schwartz, and Lior Wolf
    CVPR, 2022
    paper Code