1 citations · 2 across the 9 of their papers we have counts for
9 papers
360° Image Perception with MLLMs: A Comprehensive Benchmark and a Training-Free Method
Huyen T. T. Tran, Van-Quang Nguyen, Farros Alferro +2
Multimodal Large Language Models (MLLMs) have shown impressive abilities in understanding and reasoning over conventional images. However, their perception of 360° images remains l…
CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning
Van-Quang Nguyen, Takayuki Okatani
Existing datasets for multimodal table understanding, such as MMTab, primarily provide short factual answers without explicit multi-step reasoning supervision. Models trained on th…
TB-Bench: Training and Testing Multi-Modal AI for Understanding Spatio-Temporal Traffic Behaviors from Dashcam Images/Videos
Korawat Charoenpitaks, Van-Quang Nguyen, Masanori Suganuma +4
The application of Multi-modal Large Language Models (MLLMs) in Autonomous Driving (AD) faces significant challenges due to their limited training on traffic-specific data and the…
KTVIC: A Vietnamese Image Captioning Dataset on the Life Domain
Anh-Cuong Pham, Van-Quang Nguyen, Thi-Hong Vuong +1
Image captioning is a crucial task with applications in a wide range of domains, including healthcare and education. Despite extensive research on English image captioning datasets…
Exploring the Potential of Multi-Modal AI for Driving Hazard Prediction
Korawat Charoenpitaks, Van-Quang Nguyen, Masanori Suganuma +3
This paper addresses the problem of predicting hazards that drivers may encounter while driving a car. We formulate it as a task of anticipating impending accidents using a single…
Leveraging Video Coding Knowledge for Deep Video Enhancement
Thong Bach, Thuong Nguyen Canh, Van-Quang Nguyen
Recent advancements in deep learning techniques have significantly improved the quality of compressed videos. However, previous approaches have not fully exploited the motion chara…
GRIT: Faster and Better Image captioning Transformer Using Dual Visual Features
Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani
Current state-of-the-art methods for image captioning employ region-based features, as they provide object-level information that is essential to describe the content of images; th…
Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks
Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani
There is a growing interest in the community in making an embodied AI agent perform a complicated task while interacting with an environment following natural language directives.…
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs
Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani
It has been a primary concern in recent studies of vision and language tasks to design an effective attention mechanism dealing with interactions between the two modalities. The Tr…