activity
20182026
most citedDeep Learning Based Vehicle Make-Model Classification

12 citations · 21 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2026

Cultural Moment Benchmark: Evaluating Video Cultural Reasoning and Grounding in Southeast Asia

Burak Satar, Zhixin Ma, Cheng Yu-Tong +3

Cultural understanding in video means more than recognizing what is visible; it requires grasping the symbolic and temporal significance of cultural concepts. We decompose this int…

cs.CV2025

Seeing Culture: A Benchmark for Visual Reasoning and Grounding

Burak Satar, Zhixin Ma, Patrick A. Irawan +4

Multimodal vision-language models (VLMs) have made substantial progress in various tasks that require a combined understanding of visual and textual content, particularly in cultur…

cs.CV2024★ 1 cited

VG-TVP: Multimodal Procedural Planning via Visually Grounded Text-Video Prompting

Muhammet Furkan Ilaslan, Ali Koksal, Kevin Qinhong Lin +3

Large Language Model (LLM)-based agents have shown promise in procedural tasks, but the potential of multimodal instructions augmented by texts and videos to assist users remains u…

cs.CV2023

Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention

Burak Satar, Hongyuan Zhu, Hanwang Zhang +1

Many studies focus on improving pretraining or developing new backbones in text-video retrieval. However, existing methods may suffer from the learning and inference bias issue, as…

cs.CV2023

An Overview of Challenges in Egocentric Text-Video Retrieval

Burak Satar, Hongyuan Zhu, Hanwang Zhang +1

Text-video retrieval contains various challenges, including biases coming from diverse sources. We highlight some of them supported by illustrations to open a discussion. Besides,…

cs.CV2022★ 6 cited

Semantic Role Aware Correlation Transformer for Text to Video Retrieval

Burak Satar, Hongyuan Zhu, Xavier Bresson +1

With the emergence of social media, voluminous video clips are uploaded every day, and retrieving the most relevant visual content with a language query becomes critical. Most appr…

cs.CV2022★ 1 cited

RoME: Role-aware Mixture-of-Expert Transformer for Text-to-Video Retrieval

Burak Satar, Hongyuan Zhu, Hanwang Zhang +1

Seas of videos are uploaded daily with the popularity of social channels; thus, retrieving the most related video contents with user textual queries plays a more crucial role. Most…

cs.CV2022★ 1 cited

Exploiting Semantic Role Contextualized Video Features for Multi-Instance Text-Video Retrieval EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022

Burak Satar, Hongyuan Zhu, Hanwang Zhang +1

In this report, we present our approach for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022. We first parse sentences into semantic roles corresponding to verbs and nouns…

cs.CV2018★ 12 cited

Deep Learning Based Vehicle Make-Model Classification

Burak Satar, Ahmet Emir Dirik

This paper studies the problems of vehicle make & model classification. Some of the main challenges are reaching high classification accuracy and reducing the annotation time of th…