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20212026
most citedRecent Advances of Continual Learning in Computer Vision: An Overview

41 citations · 59 across the 27 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CV2025

Learning to Generate Cross-Task Unexploitable Examples

Haoxuan Qu, Qiuchi Xiang, Yujun Cai +4

Unexploitable example generation aims to transform personal images into their unexploitable (unlearnable) versions before they are uploaded online, thereby preventing unauthorized…

cs.CV2025

A Mixed-Primitive-based Gaussian Splatting Method for Surface Reconstruction

Haoxuan Qu, Yujun Cai, Hossein Rahmani +3

Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, exist…

cs.CV2025

TSTMotion: Training-free Scene-aware Text-to-motion Generation

Ziyan Guo, Haoxuan Qu, Hossein Rahmani +4

Text-to-motion generation has recently garnered significant research interest, primarily focusing on generating human motion sequences in blank backgrounds. However, human motions…

cs.CV2025

An Image-like Diffusion Method for Human-Object Interaction Detection

Xiaofei Hui, Haoxuan Qu, Hossein Rahmani +1

Human-object interaction (HOI) detection often faces high levels of ambiguity and indeterminacy, as the same interaction can appear vastly different across different human-object p…

cs.CV2025

CMMLoc: Advancing Text-to-PointCloud Localization with Cauchy-Mixture-Model Based Framework

Yanlong Xu, Haoxuan Qu, Jun Liu +2

The goal of point cloud localization based on linguistic description is to identify a 3D position using textual description in large urban environments, which has potential applica…

cs.CV2025

HyLiFormer: Hyperbolic Linear Attention for Skeleton-based Human Action Recognition

Yue Li, Haoxuan Qu, Mengyuan Liu +2

Transformers have demonstrated remarkable performance in skeleton-based human action recognition, yet their quadratic computational complexity remains a bottleneck for real-world a…