11 citations · 33 across the 16 of their papers we have counts for
16 papers
AetheRock: An Arm-Worn Robot Teaching System for Force-Guided Vision-Tactile Learning
Hong Li, Yue Xu, Yihan Tang +8
Force and tactile sensing are indispensable in contact-rich manipulation. However, force-aware robot learning faces critical challenges due to the incompatible assembly of tactile…
EgoGuide: Egocentric Guidance for Efficient Robot-Free Demonstration Collection and Learning
Yue Xu, Mingtao Nie, Tianle Li +4
Robot learning from real-world demonstrations is currently constrained by data scaling. Universal Manipulation Interface (UMI) provides an efficient robot-free data collection inte…
Tac-DINO: Learning Vision-Tactile Features with Patch Alignment
Hong Li, Yankang Dong, Yue Xu +8
Touch is the primary medium through which humans interact with the environment. Currently, tactile learning mainly focuses on image-level pretraining or alignment. However, tactile…
exUMI: Extensible Robot Teaching System with Action-aware Task-agnostic Tactile Representation
Yue Xu, Litao Wei, Pengyu An +2
Tactile-aware robot learning faces critical challenges in data collection and representation due to data scarcity and sparsity, and the absence of force feedback in existing system…
Take A Step Back: Rethinking the Two Stages in Visual Reasoning
Mingyu Zhang, Jiting Cai, Mingyu Liu +3
Visual reasoning, as a prominent research area, plays a crucial role in AI by facilitating concept formation and interaction with the world. However, current works are usually carr…
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Yue Xu, Zhilin Lin, Yusong Qiu +2
Though dataset distillation has witnessed rapid development in recent years, the distillation of multimodal data, e.g., image-text pairs, poses unique and under-explored challenges…
Dancing with Still Images: Video Distillation via Static-Dynamic Disentanglement
Ziyu Wang, Yue Xu, Cewu Lu +1
Recently, dataset distillation has paved the way towards efficient machine learning, especially for image datasets. However, the distillation for videos, characterized by an exclus…
EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding
Yue Xu, Yong-Lu Li, Zhemin Huang +4
With the surge in attention to Egocentric Hand-Object Interaction (Ego-HOI), large-scale datasets such as Ego4D and EPIC-KITCHENS have been proposed. However, most current research…
Towards Generic and Controllable Attacks Against Object Detection
Guopeng Li, Yue Xu, Jian Ding +1
Existing adversarial attacks against Object Detectors (ODs) suffer from two inherent limitations. Firstly, ODs have complicated meta-structure designs, hence most advanced attacks…
Distill Gold from Massive Ores: Bi-level Data Pruning towards Efficient Dataset Distillation
Yue Xu, Yong-Lu Li, Kaitong Cui +4
Data-efficient learning has garnered significant attention, especially given the current trend of large multi-modal models. Recently, dataset distillation has become an effective a…
Feature Extraction Matters More: Universal Deepfake Disruption through Attacking Ensemble Feature Extractors
Long Tang, Dengpan Ye, Zhenhao Lu +4
Adversarial example is a rising way of protecting facial privacy security from deepfake modification. To prevent massive facial images from being illegally modified by various deep…
Beyond Object Recognition: A New Benchmark towards Object Concept Learning
Yong-Lu Li, Yue Xu, Xinyu Xu +4
Understanding objects is a central building block of artificial intelligence, especially for embodied AI. Even though object recognition excels with deep learning, current machines…
Constructing Balance from Imbalance for Long-tailed Image Recognition
Yue Xu, Yong-Lu Li, Jiefeng Li +1
Long-tailed image recognition presents massive challenges to deep learning systems since the imbalance between majority (head) classes and minority (tail) classes severely skews th…
HAKE: A Knowledge Engine Foundation for Human Activity Understanding
Yong-Lu Li, Xinpeng Liu, Xiaoqian Wu +6
Human activity understanding is of widespread interest in artificial intelligence and spans diverse applications like health care and behavior analysis. Although there have been ad…
PaStaNet: Toward Human Activity Knowledge Engine
Yong-Lu Li, Liang Xu, Xinpeng Liu +7
Existing image-based activity understanding methods mainly adopt direct mapping, i.e. from image to activity concepts, which may encounter performance bottleneck since the huge gap…
Symmetry and Group in Attribute-Object Compositions
Yong-Lu Li, Yue Xu, Xiaohan Mao +1
Attributes and objects can compose diverse compositions. To model the compositional nature of these general concepts, it is a good choice to learn them through transformations, suc…