activity
20202024
most citedFlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation

9 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

DocVLM: Make Your VLM an Efficient Reader

Mor Shpigel Nacson, Aviad Aberdam, Roy Ganz +5

Vision-Language Models (VLMs) excel in diverse visual tasks but face challenges in document understanding, which requires fine-grained text processing. While typical visual tasks p…

cs.CV2024

TAP-VL: Text Layout-Aware Pre-training for Enriched Vision-Language Models

Jonathan Fhima, Elad Ben Avraham, Oren Nuriel +4

Vision-Language (VL) models have garnered considerable research interest; however, they still face challenges in effectively handling text within images. To address this limitation…

cs.CL2024

M3T: A New Benchmark Dataset for Multi-Modal Document-Level Machine Translation

Benjamin Hsu, Xiaoyu Liu, Huayang Li +6

Document translation poses a challenge for Neural Machine Translation (NMT) systems. Most document-level NMT systems rely on meticulously curated sentence-level parallel data, assu…

cs.CV2024

Question Aware Vision Transformer for Multimodal Reasoning

Roy Ganz, Yair Kittenplon, Aviad Aberdam +4

Vision-Language (VL) models have gained significant research focus, enabling remarkable advances in multimodal reasoning. These architectures typically comprise a vision encoder, a…

cs.CV2023

Towards Models that Can See and Read

Roy Ganz, Oren Nuriel, Aviad Aberdam +3

Visual Question Answering (VQA) and Image Captioning (CAP), which are among the most popular vision-language tasks, have analogous scene-text versions that require reasoning from t…

cs.CV2022★ 1 cited

Towards Weakly-Supervised Text Spotting using a Multi-Task Transformer

Yair Kittenplon, Inbal Lavi, Sharon Fogel +3

Text spotting end-to-end methods have recently gained attention in the literature due to the benefits of jointly optimizing the text detection and recognition components. Existing…

cs.CV2020★ 9 cited

FlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation

Yair Kittenplon, Yonina C. Eldar, Dan Raviv

Estimating the 3D motion of points in a scene, known as scene flow, is a core problem in computer vision. Traditional learning-based methods designed to learn end-to-end 3D flow of…