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21 papers · 1 filter
Regress Before Construct: Regress Autoencoder for Point Cloud Self-supervised Learning
Yang Liu, Chen Chen, Can Wang +2
Masked Autoencoders (MAE) have demonstrated promising performance in self-supervised learning for both 2D and 3D computer vision. Nevertheless, existing MAE-based methods still hav…
Illumination-insensitive Binary Descriptor for Visual Measurement Based on Local Inter-patch Invariance
Xinyu Lin, Yingjie Zhou, Xun Zhang +2
Binary feature descriptors have been widely used in various visual measurement tasks, particularly those with limited computing resources and storage capacities. Existing binary de…
Level-line Guided Edge Drawing for Robust Line Segment Detection
Xinyu Lin, Yingjie Zhou, Yipeng Liu +1
Line segment detection plays a cornerstone role in computer vision tasks. Among numerous detection methods that have been recently proposed, the ones based on edge drawing attract…
Unsupervised Seismic Footprint Removal With Physical Prior Augmented Deep Autoencoder
Feng Qian, Yuehua Yue, Yu He +4
Seismic acquisition footprints appear as stably faint and dim structures and emerge fully spatially coherent, causing inevitable damage to useful signals during the suppression pro…
NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery
Ming Lu, Leyuan Fang, Muxing Li +3
The use of deep learning for water extraction requires precise pixel-level labels. However, it is very difficult to label high-resolution remote sensing images at the pixel level.…
Indicative Image Retrieval: Turning Blackbox Learning into Grey
Xulu Zhang, Zhenqun Yang, Hao Tian +2
Deep learning became the game changer for image retrieval soon after it was introduced. It promotes the feature extraction (by representation learning) as the core of image retriev…