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20202025
most citedUnderstanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

25 citations · 28 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

SMPL Normal Map Is All You Need for Single-view Textured Human Reconstruction

Wenhao Shen, Gangjian Zhang, Jianfeng Zhang +4

Single-view textured human reconstruction aims to reconstruct a clothed 3D digital human by inputting a monocular 2D image. Existing approaches include feed-forward methods, limite…

cs.CV2025★ 1 cited

ProbDiffFlow: An Efficient Learning-Free Framework for Probabilistic Single-Image Optical Flow Estimation

Mo Zhou, Jianwei Wang, Xuanmeng Zhang +5

This paper studies optical flow estimation, a critical task in motion analysis with applications in autonomous navigation, action recognition, and film production. Traditional opti…

cs.CV2023★ 1 cited

GETAvatar: Generative Textured Meshes for Animatable Human Avatars

Xuanmeng Zhang, Jianfeng Zhang, Rohan Chacko +4

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries. Generally, two challenges remain…

cs.CV2022

Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis

Xuanmeng Zhang, Zhedong Zheng, Daiheng Gao +3

3D-aware image synthesis aims to generate images of objects from multiple views by learning a 3D representation. However, one key challenge remains: existing approaches lack geomet…

cs.CV2020★ 25 cited

Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

Xuanmeng Zhang, Minyue Jiang, Zhedong Zheng +3

The re-ranking approach leverages high-confidence retrieved samples to refine retrieval results, which have been widely adopted as a post-processing tool for image retrieval tasks.…