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Pha Nguyen

7 accepted papers

2025

HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation

CVPR 2025poster

Multimodal LLMs have advanced vision-language tasks but still struggle with understanding video scenes. To bridge this gap, Video Scene Graph Generation (VidSGG) has emerged to capture multi-object relationships across video frames. However, prior methods rely on pairwise connections, limiting their…

Cited by 1SourcePDFScholar
2024

CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos

NeurIPS 2024poster

Video scene graph generation (VidSGG) has emerged as a transformative approach to capturing and interpreting the intricate relationships among objects and their temporal dynamics in video sequences. In this paper, we introduce the new AeroEye dataset that focuses on multi-object relationship modelin…

Cited by 3SourcePDFScholar
2024

DINTR: Tracking via Diffusion-based Interpolation

NeurIPS 2024poster

Object tracking is a fundamental task in computer vision, requiring the localization of objects of interest across video frames. Diffusion models have shown remarkable capabilities in visual generation, making them well-suited for addressing several requirements of the tracking problem. This work pr…

Cited by 0SourcePDFScholar
2024

HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding

CVPR 2024poster

Visual interactivity understanding within visual scenes presents a significant challenge in computer vision. Existing methods focus on complex interactivities while leveraging a simple relationship model. These methods however struggle with a diversity of appearance situation position interaction an…

Cited by 14SourcePDFScholar
2024

Z-GMOT: Zero-shot Generic Multiple Object Tracking

NAACL 2024findings

Despite recent significant progress, Multi-Object Tracking (MOT) faces limitations such as reliance on prior knowledge and predefined categories and struggles with unseen objects. To address these issues, Generic Multiple Object Tracking (GMOT) has emerged as an alternative approach, requiring less…

2023

Type-to-Track: Retrieve Any Object via Prompt-based Tracking

NeurIPS 2023poster

One of the recent trends in vision problems is to use natural language captions to describe the objects of interest. This approach can overcome some limitations of traditional methods that rely on bounding boxes or category annotations. This paper introduces a novel paradigm for Multiple Object Trac…

Cited by 24SourcePDFScholar
2021

DyGLIP: A Dynamic Graph Model With Link Prediction for Accurate Multi-Camera Multiple Object Tracking

CVPR 2021poster

Multi-Camera Multiple Object Tracking (MC-MOT) is a significant computer vision problem due to its emerging applicability in several real-world applications. Despite a large number of existing works, solving the data association problem in any MC-MOT pipeline is arguably one of the most challenging…

Cited by 71PDFcodeScholar