4 citations · 5 across the 13 of their papers we have counts for
13 papers
SurgNarrator: A Generative Retrieval Framework for Surgical Video Understanding
Yuqing Feng, Jiawei Ma, Kevin Qinghong Lin +6
Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for intraoperative decision-mak…
OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMs
Hao Vo, Phu Loc Nguyen, Khoa Vo +7
Multimodal Large Language Models (MLLMs) have achieved remarkable performance on 2D visual tasks, yet enhancing their spatial intelligence for real-world applications such as Auton…
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving
Hao Vo, Khoa Vo, Phu Loc Nguyen +10
Spatiotemporal intelligence in autonomous driving (AD) requires an agent to integrate multi-view observations into a coherent scene representation, maintain object continuity acros…
SemLT3D: Semantic-Guided Expert Distillation for Camera-only Long-Tailed 3D Object Detection
Hao Vo, Khoa Vo, Thinh Phan +5
Camera-only 3D object detection has emerged as a cost-effective and scalable alternative to LiDAR for autonomous driving, yet existing methods primarily prioritize overall performa…
CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models
Khoa Vo, Sieu Tran, Taisei Hanyu +8
Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume the latest observation is su…
PolypSteer: Counterfactual Endoscopic Synthesis via Training-Free Activation Steering
Trong-Thang Pham, Loc Nguyen, Anh Nguyen +2
Generative diffusion models are increasingly used for medical imaging data augmentation, but text prompting cannot produce causal training data. Re-prompting rerolls the entire gen…
Clutter-Robust Vision-Language-Action Models through Object-Centric and Geometry Grounding
Khoa Vo, Taisei Hanyu, Yuki Ikebe +8
Recent Vision-Language-Action (VLA) models have made impressive progress toward general-purpose robotic manipulation by post-training large Vision-Language Models (VLMs) for action…
Rethinking Progression of Memory State in Robotic Manipulation: An Object-Centric Perspective
Nhat Chung, Taisei Hanyu, Toan Nguyen +9
As embodied agents operate in increasingly complex environments, the ability to perceive, track, and reason about individual object instances over time becomes essential, especiall…
SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation
Taisei Hanyu, Nhat Chung, Huy Le +10
Inspired by how humans reason over discrete objects and their relationships, we explore whether compact object-centric and object-relation representations can form a foundation for…
BiMa: Towards Biases Mitigation for Text-Video Retrieval via Scene Element Guidance
Huy Le, Nhat Chung, Tung Kieu +2
Text-video retrieval (TVR) systems often suffer from visual-linguistic biases present in datasets, which cause pre-trained vision-language models to overlook key details. To addres…
FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
Trong Thang Pham, Ngoc-Vuong Ho, Nhat-Tan Bui +8
Developing an interpretable system for generating reports in chest X-ray (CXR) analysis is becoming increasingly crucial in Computer-aided Diagnosis (CAD) systems, enabling radiolo…
WAVER: Writing-style Agnostic Text-Video Retrieval via Distilling Vision-Language Models Through Open-Vocabulary Knowledge
Huy Le, Tung Kieu, Anh Nguyen +1
Text-video retrieval, a prominent sub-field within the domain of multimodal information retrieval, has witnessed remarkable growth in recent years. However, existing methods assume…
Open-Fusion: Real-time Open-Vocabulary 3D Mapping and Queryable Scene Representation
Kashu Yamazaki, Taisei Hanyu, Khoa Vo +5
Precise 3D environmental mapping is pivotal in robotics. Existing methods often rely on predefined concepts during training or are time-intensive when generating semantic maps. Thi…