activity
20142023
most citedDebiased Self-Training for Semi-Supervised Learning

39 citations · 167 across the 20 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021

Assessing a Single Image in Reference-Guided Image Synthesis

Jiayi Guo, Chaoqun Du, Jiangshan Wang +3

Assessing the performance of Generative Adversarial Networks (GANs) has been an important topic due to its practical significance. Although several evaluation metrics have been pro…

cs.CV2021★ 12 cited

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation

Mingcong Liu, Qiang Li, Zekui Qin +3

Generative Adversarial Networks (GANs) have made a dramatic leap in high-fidelity image synthesis and stylized face generation. Recently, a layer-swapping mechanism has been develo…

cs.CV2021★ 3 cited

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

Peng Xiang, Xin Wen, Yu-Shen Liu +4

Point cloud completion aims to predict a complete shape in high accuracy from its partial observation. However, previous methods usually suffered from discrete nature of point clou…

cs.CV2021★ 1 cited

Exploring Set Similarity for Dense Self-supervised Representation Learning

Zhaoqing Wang, Qiang Li, Guoxin Zhang +5

By considering the spatial correspondence, dense self-supervised representation learning has achieved superior performance on various dense prediction tasks. However, the pixel-lev…

cs.CV2021★ 5 cited

Camera-Space Hand Mesh Recovery via Semantic Aggregation and Adaptive 2D-1D Registration

Xingyu Chen, Yufeng Liu, Chongyang Ma +6

Recent years have witnessed significant progress in 3D hand mesh recovery. Nevertheless, because of the intrinsic 2D-to-3D ambiguity, recovering camera-space 3D information from a…

cs.CV2021★ 9 cited

Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding

Xin Wen, Zhizhong Han, Yan-Pei Cao +3

In this paper, we present a novel unpaired point cloud completion network, named Cycle4Completion, to infer the complete geometries from a partial 3D object. Previous unpaired comp…