3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2023
SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operations
Pu Li, Jianwei Guo, Xiaopeng Zhang +1
Reverse engineering CAD models from raw geometry is a classic but strenuous research problem. Previous learning-based methods rely heavily on labels due to the supervised design pa…
cs.CV2023★ 3 cited
Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentation
Rongtao Xu, Changwei Wang, Jiaxi Sun +3
Efficiently training accurate deep models for weakly supervised semantic segmentation (WSSS) with image-level labels is challenging and important. Recently, end-to-end WSSS methods…
cs.CV2022
SdAE: Self-distillated Masked Autoencoder
Yabo Chen, Yuchen Liu, Dongsheng Jiang +4
With the development of generative-based self-supervised learning (SSL) approaches like BeiT and MAE, how to learn good representations by masking random patches of the input image…