4 citations · 12 across the 32 of their papers we have counts for
34 papers
TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning
Dayou Li, Hao Wang, Qianqian Yang +23
Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the contact and pressure that ch…
Counting Beyond Instances: A Benchmark for Group-Individual Object Counting
Rui Wang, Junyi Huang, Jiahui Li +4
Visual counting is commonly formulated at the instance level, aiming to estimate how many objects of a queried category appear in an image. However, real-world counting often invol…
Gripper-aware Vision Language Action Models
Hanyi Zhang, Zihong Luo, Tianyu Li +16
Vision language action models (VLAs) have advanced general purpose robotic grasping and manipulation by enabling robots to interpret visual observations and natural language instru…
Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution
Hanyi Zhang, Khang Nguyen, Charith Munasinghe +10
Robust robotic grasping remains a fundamental challenge for complex real-world applications. Recent advances in large-scale models demonstrate promising capabilities for reasoning…
SARA: Semantically Adaptive Relational Alignment for Video Diffusion Models
Jiesong Lian, Zixiang Zhou, Ruizhe Zhong +6
Recent video diffusion models (VDMs) synthesize visually convincing clips, yet still drop entities, mis-bind attributes, and weaken the interactions specified in the prompt. Repres…
CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Outdoor robot teams need a shared dense map despite limited overlap, independent reference frames, and uncertain monocular scale. Collaborative dense SLAM systems typically resolve…
MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While re…
AffordMatcher: Affordance Learning in 3D Scenes from Visual Signifiers
Nghia Vu, Tuong Do, Khang Nguyen +8
Affordance learning is a complex challenge in many applications, where existing approaches primarily focus on the geometric structures, visual knowledge, and affordance labels of o…
SIGMA: A Physics-Based Benchmark for Gas Chimney Understanding in Seismic Images
Bao Truong, Quang Nguyen, Baoru Huang +6
Seismic images reconstruct subsurface reflectivity from field recordings, guiding exploration and reservoir monitoring. Gas chimneys are vertical anomalies caused by subsurface flu…
Pessimistic Auxiliary Policy for Offline Reinforcement Learning
Fan Zhang, Baoru Huang, Xin Zhang
Offline reinforcement learning aims to learn an agent from pre-collected datasets, avoiding unsafe and inefficient real-time interaction. However, inevitable access to out-ofdistri…
CADKnitter: Compositional CAD Generation from Text and Geometry Guidance
Tri Le, Khang Nguyen, Baoru Huang +2
Computer-aided design (CAD) defines 3D models as compact, precise, and editable representations, making it directly useful for several fields. Recently, CAD generation has been gai…
Learning Human Motion with Temporally Conditional Mamba
Quang Nguyen, Tri Le, Baoru Huang +4
Learning human motion based on a time-dependent input signal presents a challenging yet impactful task with various applications. The goal of this task is to generate or estimate h…
EgoMusic-driven Human Dance Motion Estimation with Skeleton Mamba
Quang Nguyen, Nhat Le, Baoru Huang +6
Estimating human dance motion is a challenging task with various industrial applications. Recently, many efforts have focused on predicting human dance motion using either egocentr…
GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System
Quang Nguyen, Tri Le, Huy Nguyen +5
Language-driven grasp detection has the potential to revolutionize human-robot interaction by allowing robots to understand and execute grasping tasks based on natural language com…
Humanoid Agent via Embodied Chain-of-Action Reasoning with Multimodal Foundation Models for Zero-Shot Loco-Manipulation
Congcong Wen, Geeta Chandra Raju Bethala, Yu Hao +8
Humanoid loco-manipulation, which integrates whole-body locomotion with dexterous manipulation, remains a fundamental challenge in robotics. Beyond whole-body coordination and bala…
RoboDesign1M: A Large-scale Dataset for Robot Design Understanding
Tri Le, Toan Nguyen, Quang Tran +6
Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can enable various applications, inclu…
FedEFM: Federated Endovascular Foundation Model with Unseen Data
Tuong Do, Nghia Vu, Tudor Jianu +7
In endovascular surgery, the precise identification of catheters and guidewires in X-ray images is essential for reducing intervention risks. However, accurately segmenting cathete…
SplineFormer: An Explainable Transformer-Based Approach for Autonomous Endovascular Navigation
Tudor Jianu, Shayan Doust, Mengyun Li +8
Endovascular navigation is a crucial aspect of minimally invasive procedures, where precise control of curvilinear instruments like guidewires is critical for successful interventi…
Nested ResNet: A Vision-Based Method for Detecting the Sensing Area of a Drop-in Gamma Probe
Songyu Xu, Yicheng Hu, Jionglong Su +2
Purpose: Drop-in gamma probes are widely used in robotic-assisted minimally invasive surgery (RAMIS) for lymph node detection. However, these devices only provide audio feedback on…
Guide3D: A Bi-planar X-ray Dataset for 3D Shape Reconstruction
Tudor Jianu, Baoru Huang, Hoan Nguyen +8
Endovascular surgical tool reconstruction represents an important factor in advancing endovascular tool navigation, which is an important step in endovascular surgery. However, the…
Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applications
Nghia Nguyen, Minh Nhat Vu, Tung D. Ta +4
Vision language models have played a key role in extracting meaningful features for various robotic applications. Among these, Contrastive Language-Image Pretraining (CLIP) is wide…
CathAction: A Benchmark for Endovascular Intervention Understanding
Baoru Huang, Tuan Vo, Chayun Kongtongvattana +35
Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are of…
Language-driven Grasp Detection with Mask-guided Attention
Tuan Van Vo, Minh Nhat Vu, Baoru Huang +4
Grasp detection is an essential task in robotics with various industrial applications. However, traditional methods often struggle with occlusions and do not utilize language for g…
Lightweight Language-driven Grasp Detection using Conditional Consistency Model
Nghia Nguyen, Minh Nhat Vu, Baoru Huang +4
Language-driven grasp detection is a fundamental yet challenging task in robotics with various industrial applications. In this work, we present a new approach for language-driven…