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20162024
most citedMasked Modeling for Self-supervised Representation Learning on Vision and Beyond

7 citations · 9 across the 9 of their papers we have counts for

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cs.CV2024

StyleDyRF: Zero-shot 4D Style Transfer for Dynamic Neural Radiance Fields

Hongbin Xu, Weitao Chen, Feng Xiao +2

4D style transfer aims at transferring arbitrary visual style to the synthesized novel views of a dynamic 4D scene with varying viewpoints and times. Existing efforts on 3D style t…

cs.CV2024

FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation

Pengchong Qiao, Lei Shang, Chang Liu +3

Subject-driven generation has garnered significant interest recently due to its ability to personalize text-to-image generation. Typical works focus on learning the new subject's p…

cs.CV2024

PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation

Haoyu Xie, Changqi Wang, Jian Zhao +4

Tremendous breakthroughs have been developed in Semi-Supervised Semantic Segmentation (S4) through contrastive learning. However, due to limited annotations, the guidance on unlabe…

cs.CV20247 cited

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond

Siyuan Li, Luyuan Zhang, Zedong Wang +8

As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and…

cs.CV20231 cited

CostFormer:Cost Transformer for Cost Aggregation in Multi-view Stereo

Weitao Chen, Hongbin Xu, Zhipeng Zhou +4

The core of Multi-view Stereo(MVS) is the matching process among reference and source pixels. Cost aggregation plays a significant role in this process, while previous methods focu…

cs.CV2021

TransZero: Attribute-guided Transformer for Zero-Shot Learning

Shiming Chen, Ziming Hong, Yang Liu +6

Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen ones. Semantic knowledge is learned from attribute descripti…