43 citations · 80 across the 43 of their papers we have counts for
48 papers
Physics-Aware Object-Centric SE(3) Forecasting for Real-Time Proactive Dynamic Grasping
Yirui Zhou, Hongli Xu, Ying Zheng +2
Proactive dynamic grasping requires robots to predict the future state at which physical contact will occur, rather than reacting to the currently observed object pose. But what fu…
UniLAP: A Unified Latent Action Policy for Cross-Embodiment Manipulation
Lei Yao, Qiao Feng, Mutian Tong +3
Latent Action Models (LAMs) can capture manipulation priors from action-free videos, but discrete latents usually impose a granularity bottleneck, limiting their ability to represe…
Have You Seen It Clearly? Uncertainty-Guided Belief Refinement for Zero-Shot Object Navigation
Jingzhi Huang, Junkai Huang, Yuhang Peng +6
Zero-Shot Object Navigation (ZSON) requires an agent to locate target objects in unfamiliar environments without additional training for the test categories or environments. Recent…
SeqAlign3DVG: A Sequence-Aligned Benchmark and Voxel Reasoning Framework for 3D Visual Grounding
Yi Zhang, Yi Wang, Yueting Wu +3
Image-based 3D visual grounding is critical for embodied agents, yet existing benchmarks suffer from loose text-observation alignment and neglect temporal ordering. We introduce Se…
EgoErrorVQA: Assess Egocentric Comprehension Capabilities through Procedural Errors for Ego-Agentic AI
Junlong Li, Junxi Li, Jianjun Gao +3
The majority of our everyday activities are procedural and consist of sequences of interdependent steps. However, existing benchmarks for Visual Agents and Visual Language Models (…
EgoProceVQA: A Novel Egocentric Procedural Understanding Task with Self-Skill-Exploration Agent
Junlong Li, Junxi Li, Yuxiang Yang +3
Most daily activities are inherently procedural. However, existing evaluations for egocentric video understanding seldom address procedural understanding and largely overlook compl…
TextDS: Parameter-Efficient Representation Alignment for Scene Text Detection under Distribution Shifts
Boyuan Chen, Zichen Dang, Chuang Yang +2
In real-world deployments, scene text detectors inevitably face distribution shifts beyond the training distribution. Prior work often depends on large-scale scene-text pretraining…
GUI-C: Coarse-to-Fine GUI Grounding via Difficulty-Aware Reinforcement Learning
Junlong Li, Chao Hao, Lap-Pui Chau +1
Existing agentic reinforcement learning methods for GUI grounding have limitations at two levels. At the data level, current approaches typically treat all training samples equally…
SP-MoMamba: Superpixel-driven Mixture of State Space Experts for Efficient Image Super-Resolution
Wenbin Zou, Yawen Cui, Yi Wang +5
State space models (SSMs) have emerged as an efficient paradigm for single-image super-resolution (SR) due to their linear complexity and long-range modeling capabilities. However,…
RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation
Sixu Lin, Junliang Chen, Huaiyuan Xu +8
Planning and acting in 3D environments is a fundamental capability for robotic manipulation in the real world. Although prior work has explored predictive flow planners to guide 3D…
EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding
Yuejiao Su, Xinshen Zhang, Zhen Ye +3
Understanding human--environment interactions from egocentric vision is essential for assistive robotics and embodied intelligent agents, yet existing multimodal large language mod…
LLM-Agnostic Semantic Representation Attack
Jiawei Lian, Jianhong Pan, Lefan Wang +4
Large Language Models (LLMs) increasingly employ alignment techniques to prevent harmful outputs. Despite these safeguards, attackers can circumvent them by crafting adversarial pr…
Evolution-Inspired Sample Competition for Deep Neural Network Optimization
Ying Zheng, Yiyi Zhang, Yi Wang +1
Conventional deep network training generally optimizes all samples under a largely uniform learning paradigm, without explicitly modeling the heterogeneous competition among them.…
NTIRE 2026 Challenge on Bitstream-Corrupted Video Restoration: Methods and Results
Wenbin Zou, Tianyi Liu, Kejun Wu +37
This paper reports on the NTIRE 2026 Challenge on Bitstream-Corrupted Video Restoration (BSCVR). The challenge aims to advance research on recovering visually coherent videos from…
MASS: Mesh-inellipse Aligned Deformable Surfel Splatting for Hand Reconstruction and Rendering from Egocentric Monocular Video
Haoyu Zhu, Yi Zhang, Lei Yao +2
Reconstructing high-fidelity 3D hands from egocentric monocular videos remains a challenge due to the limitations in capturing high-resolution geometry, hand-object interactions, a…
HVG-3D: Bridging Real and Simulation Domains for 3D-Conditional Hand-Object Interaction Video Synthesis
Mingjin Chen, Junhao Chen, Zhaoxin Fan +6
Recent methods have made notable progress in the visual quality of hand-object interaction video synthesis. However, most approaches rely on 2D control signals that lack spatial ex…
Accelerating Diffusion-based Video Editing via Heterogeneous Caching: Beyond Full Computing at Sampled Denoising Timestep
Tianyi Liu, Ye Lu, Linfeng Zhang +5
Diffusion-based video editing has emerged as an important paradigm for high-quality and flexible content generation. However, despite their generality and strong modeling capacity,…
ProCal: Probability Calibration for Neighborhood-Guided Source-Free Domain Adaptation
Ying Zheng, Yiyi Zhang, Yi Wang +1
Source-Free Domain Adaptation (SFDA) adapts pre-trained models to unlabeled target domains without requiring access to source data. Although state-of-the-art methods leveraging loc…
HAMMER: Harnessing MLLM via Cross-Modal Integration for Intention-Driven 3D Affordance Grounding
Lei Yao, Yong Chen, Yuejiao Su +3
Humans commonly identify 3D object affordance through observed interactions in images or videos, and once formed, such knowledge can be generically generalized to novel objects. In…
Interaction-aware Representation Modeling with Co-occurrence Consistency for Egocentric Hand-Object Parsing
Yuejiao Su, Yi Wang, Lei Yao +2
A fine-grained understanding of egocentric human-environment interactions is crucial for developing next-generation embodied agents. One fundamental challenge in this area involves…
LaSSM: Efficient Semantic-Spatial Query Decoding via Local Aggregation and State Space Models for 3D Instance Segmentation
Lei Yao, Yi Wang, Yawen Cui +2
Query-based 3D scene instance segmentation from point clouds has attained notable performance. However, existing methods suffer from the query initialization dilemma due to the spa…
GVSynergy-Det: Synergistic Gaussian-Voxel Representations for Multi-View 3D Object Detection
Yi Zhang, Yi Wang, Lei Yao +1
Image-based 3D object detection aims to identify and localize objects in 3D space using only RGB images, eliminating the need for expensive depth sensors required by point cloud-ba…
Building Egocentric Procedural AI Assistant: Methods, Benchmarks, and Challenges
Junlong Li, Huaiyuan Xu, Sijie Cheng +4
Driven by recent advances in vision-language models (VLMs) and egocentric perception research, the emerging topic of an egocentric procedural AI assistant (EgoProceAssist) is intro…
Semantic Representation Attack against Aligned Large Language Models
Jiawei Lian, Jianhong Pan, Lefan Wang +3
Large Language Models (LLMs) increasingly employ alignment techniques to prevent harmful outputs. Despite these safeguards, attackers can circumvent them by crafting prompts that i…