activity
20202026
most citedPaStaNet: Toward Human Activity Knowledge Engine

11 citations · 33 across the 16 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

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…

cs.CV2024

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…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 7 cited

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…

cs.CV2022

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…

cs.CV2022★ 1 cited

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…

cs.CV2022★ 9 cited

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…

cs.CV2020★ 11 cited

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…

cs.CV2020★ 4 cited

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…