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20172023
most citedAdaptive Context-Aware Multi-Modal Network for Depth Completion

175 citations · 280 across the 22 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CV2022

Adaptive Edge-to-Edge Interaction Learning for Point Cloud Analysis

Shanshan Zhao, Mingming Gong, Xi Li +1

Recent years have witnessed the great success of deep learning on various point cloud analysis tasks, e.g., classification and semantic segmentation. Since point cloud data is spar…

cs.CV2022★ 3 cited

DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting

Maoyuan Ye, Jing Zhang, Shanshan Zhao +4

End-to-end text spotting aims to integrate scene text detection and recognition into a unified framework. Dealing with the relationship between the two sub-tasks plays a pivotal ro…

cs.CV2022

MetaComp: Learning to Adapt for Online Depth Completion

Yang Chen, Shanshan Zhao, Wei Ji +2

Relying on deep supervised or self-supervised learning, previous methods for depth completion from paired single image and sparse depth data have achieved impressive performance in…

cs.CV2022★ 1 cited

MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis

Yaqian Liang, Shanshan Zhao, Baosheng Yu +2

Recently, self-supervised pre-training has advanced Vision Transformers on various tasks w.r.t. different data modalities, e.g., image and 3D point cloud data. In this paper, we ex…

cs.CV2022★ 3 cited

DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer

Maoyuan Ye, Jing Zhang, Shanshan Zhao +3

Recently, Transformer-based methods, which predict polygon points or Bezier curve control points for localizing texts, are popular in scene text detection. However, these methods b…

cs.CV2022

Iterative Geometry-Aware Cross Guidance Network for Stereo Image Inpainting

Ang Li, Shanshan Zhao, Qingjie Zhang +1

Currently, single image inpainting has achieved promising results based on deep convolutional neural networks. However, inpainting on stereo images with missing regions has not bee…