43 citations · 80 across the 43 of their papers we have counts for
21 papers · 1 filter
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…