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20182023
most citedMultiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network

145 citations · 570 across the 24 of their papers we have counts for

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15 papers · 1 filter

cs.CV2023

Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On

Daiheng Gao, Xu Chen, Xindi Zhang +5

Fabricating and designing 3D garments has become extremely demanding with the increasing need for synthesizing realistic dressed persons for a variety of applications, e.g. 3D virt…

cs.CV2023

PanoContext-Former: Panoramic Total Scene Understanding with a Transformer

Yuan Dong, Chuan Fang, Liefeng Bo +2

Panoramic image enables deeper understanding and more holistic perception of surrounding environment, which can naturally encode enriched scene context information comp…

cs.CV2023★ 1 cited

DiffHand: End-to-End Hand Mesh Reconstruction via Diffusion Models

Lijun Li, Li'an Zhuo, Bang Zhang +2

Hand mesh reconstruction from the monocular image is a challenging task due to its depth ambiguity and severe occlusion, there remains a non-unique mapping between the monocular im…

cs.CV2023★ 3 cited

One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field

Weichuang Li, Longhao Zhang, Dong Wang +7

Talking head generation aims to generate faces that maintain the identity information of the source image and imitate the motion of the driving image. Most pioneering methods rely…

cs.CV2023★ 2 cited

Evaluate Geometry of Radiance Fields with Low-frequency Color Prior

Qihang Fang, Yafei Song, Keqiang Li +4

A radiance field is an effective representation of 3D scenes, which has been widely adopted in novel-view synthesis and 3D reconstruction. It is still an open and challenging probl…

cs.CV2022★ 1 cited

Compressing Volumetric Radiance Fields to 1 MB

Lingzhi Li, Zhen Shen, Zhongshu Wang +2

Approximating radiance fields with volumetric grids is one of promising directions for improving NeRF, represented by methods like Plenoxels and DVGO, which achieve super-fast trai…