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Nhu-Binh Nguyen Truc

dblp:401/7106 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0007-3769-7955ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visual content generation and editing · 100%
Human-computer interaction and pervasive computing
1 paper
Personal fabrication and tangible interfaces · 100%
Artificial intelligence
1 paper
Generative modeling · 100%
Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visual content generation and editing
sketch generation
0.912025
Advancing Fashion Design Through Intelligent Sketchpad Studio · ACM Multimedia 2025
Machine learning › Generative modeling › computational creativity › creative generation
generative AI for design
0.312025
Advancing Fashion Design Through Intelligent Sketchpad Studio · ACM Multimedia 2025
Information retrieval › image retrieval
sketch-based retrieval
0.312025
Advancing Fashion Design Through Intelligent Sketchpad Studio · ACM Multimedia 2025

Methods — techniques the papers use, named apart from their topics

text-to-sketch generation · 3.5large language model · 3.5context-aware recommendation · 3.5
YearPublicationVenuePosition
2025 Advancing Fashion Design Through Intelligent Sketchpad Studio
abstract
Line sketches serve as the visual DNA of fashion design, forming the essential foundation where concepts take shape, yet today's digital tools often lack the fluidity, personalization, and intelligence needed to truly support this creative process. We present FashSketch, an interactive, multimedia-driven system that reimagines fashion sketching through the lens of generative AI. Designed with a layer-based creative interface, FashSketch empowers designers to ideate, customize, and iterate on sketches seamlessly. By integrating state-of-the-art generative models, sketch-based retrieval, and large language models, the system supports advanced functionalities such as text-to-sketch generation and context-aware sketch recommendation. FashSketch not only enhances the sketching experience but also opens new multimodal pathways for creative expression, making it a powerful co-creative partner in the early stages of fashion design. Video demo is available at https://youtu.be/BX-Edz7Z7ZY.
Nhu-Binh Nguyen Truc, Nhu-Vinh Hoang, Tam V. Nguyen 0002, Minh-Triet Tran, Trung-Nghia Le
ACM Multimedia1