Thong Nguyen

STRAND: Benchmarking and Improving Object-Centric Spatio-Temporal Monitoring in Video Large Language Models

Thong Nguyen, Tri Cao, Khoi Le +4

While multimodal large language models (MLLMs) have advanced video understanding, they remain highly prone to hallucinations in dynamic scenes. We argue this stems from a failure i…

MatReplace: A Reference-Free, Conditioning-Aligned Benchmark for Material Replacement in Interior Scenes

Mingzhe Du, Thong Thanh Nguyen, Nguyen Tran Cong Duy +2

Material replacement is a common interior-design operation: changing the material of a selected surface while preserving its geometry, surroundings, and illumination. Despite its c…

DynaPix: Can Vision-Language Models Identify the Exact Future?

Thong Nguyen, Vinh-Hien Do, Quynh Vo +2

Acting in a physical scene requires knowing its real later state, not a plausible one. Current evaluations often accept words or a realistic-looking image, so the predicted state i…

Predict, Then Retrieve: Cross-Instance Future-State Retrieval from Video Prefixes

Quynh Vo, Thong Nguyen, Vinh-Hien Do +2

We introduce Predictive State Retrieval (PSR), a task in which a model observes a short video prefix and a temporal question about an object's future state, then retrieves instance…

When Depth Is Better Told Than Shown: Depth-Ordinal Prompting for Vision-Language Spatial Reasoning

Quynh Vo, Phuc Dao, Cong-Duy Nguyen +1

Vision-language models (VLMs) are expected to reason about physical space -- which object is closer, what lies behind what, and how objects are arranged in 3D -- yet they still str…

Eulerian Motion Guidance: Robust Image Animation via Bidirectional Geometric Consistency

Thong Nguyen, Khoi M. Le, Cong-Duy Nguyen +3

Recent advancements in image animation have utilized diffusion models to breathe life into static images. However, existing controllable frameworks typically rely on Lagrangian mot…

Video Understanding: Through A Temporal Lens

Thong Thanh Nguyen

This thesis explores the central question of how to leverage temporal relations among video elements to advance video understanding. Addressing the limitations of existing methods,…

Temporal-Oriented Recipe for Transferring Large Vision-Language Model to Video Understanding

Thong Nguyen, Zhiyuan Hu, Xu Lin +3

Recent years have witnessed outstanding advances of large vision-language models (LVLMs). In order to tackle video understanding, most of them depend upon their implicit temporal u…

TI-JEPA: An Innovative Energy-based Joint Embedding Strategy for Text-Image Multimodal Systems

Khang H. N. Vo, Duc P. T. Nguyen, Thong Nguyen +1

This paper focuses on multimodal alignment within the realm of Artificial Intelligence, particularly in text and image modalities. The semantic gap between the textual and visual m…

CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base

Cong-Duy Nguyen, Xiaobao Wu, Duc Anh Vu +3

Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, but they remain susceptible to hallucination, particularly object hallucination…

Enhancing Multimodal Entity Linking with Jaccard Distance-based Conditional Contrastive Learning and Contextual Visual Augmentation

Cong-Duy Nguyen, Xiaobao Wu, Thong Nguyen +5

Previous research on multimodal entity linking (MEL) has primarily employed contrastive learning as the primary objective. However, using the rest of the batch as negative samples…

Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation

Thong Thanh Nguyen, Xiaobao Wu, Yi Bin +3

To equip artificial intelligence with a comprehensive understanding towards a temporal world, video and 4D panoptic scene graph generation abstracts visual data into nodes to repre…

Multi-Scale Contrastive Learning for Video Temporal Grounding

Thong Thanh Nguyen, Yi Bin, Xiaobao Wu +4

Temporal grounding, which localizes video moments related to a natural language query, is a core problem of vision-language learning and video understanding. To encode video moment…

MAMA: Meta-optimized Angular Margin Contrastive Framework for Video-Language Representation Learning

Thong Nguyen, Yi Bin, Xiaobao Wu +6

Data quality stands at the forefront of deciding the effectiveness of video-language representation learning. However, video-text pairs in previous data typically do not align perf…