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20192024
most citedVisual Relationship Detection with Relative Location Mining

15 citations · 29 across the 2 of their papers we have counts for

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Showing cs.CVShow all

5 papers · 1 filter

cs.CV2024

AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario

Yuhan Li, Hao Zhou, Wenxiang Shang +3

While image-based virtual try-on has made significant strides, emerging approaches still fall short of delivering high-fidelity and robust fitting images across various scenarios,…

cs.CV20231 cited

Towards Diverse Temporal Grounding under Single Positive Labels

Hao Zhou, Chongyang Zhang, Yanjun Chen +1

Temporal grounding aims to retrieve moments of the described event within an untrimmed video by a language query. Typically, existing methods assume annotations are precise and uni…

cs.CV2021

Embracing Uncertainty: Decoupling and De-bias for Robust Temporal Grounding

Hao Zhou, Chongyang Zhang, Yan Luo +2

Temporal grounding aims to localize temporal boundaries within untrimmed videos by language queries, but it faces the challenge of two types of inevitable human uncertainties: quer…

cs.CV202014 cited

Where, What, Whether: Multi-modal Learning Meets Pedestrian Detection

Yan Luo, Chongyang Zhang, Muming Zhao +2

Pedestrian detection benefits greatly from deep convolutional neural networks (CNNs). However, it is inherently hard for CNNs to handle situations in the presence of occlusion and…

cs.CV201915 cited

Visual Relationship Detection with Relative Location Mining

Hao Zhou, Chongyang Zhang, Chuanping Hu

Visual relationship detection, as a challenging task used to find and distinguish the interactions between object pairs in one image, has received much attention recently. In this…