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[1]基于全局局部协同的非均匀图像去雾方法.自动化学报,2024,50(07):1333-1344.
[2]基于全局局部协同的非均匀图像去雾方法.自动化学报,2024,1-12.
[3]QYY,AdaFormer: Efficient Transformer with Adaptive Token Sparsification for Image Super-resolution.THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 5,4009-4016.
[4]QYY,SkipDiff: Adaptive Skip Diffusion Model for High-Fidelity Perceptual Image Super-resolution.THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 5,4017-4025.
[5]QYY.Beyond the Label Itself: Latent Labels Enhance Semi-supervised Point Cloud Panoptic Segmentation.THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 2,1245-1253.
[6]QYY,Weakly Supervised 3D Segmentation via Receptive-Driven Pseudo Label Consistency and Structural Consistency.THIRTY-SEVENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 37 NO 1,1222-1230.
[7]基于全局局部协同的非均匀图像去雾方法.自动化学报,2024,1-12.
[8]QYY.Uni-to-Multi Modal Knowledge Distillation for Bidirectional LiDAR-Camera Semantic Segmentation.IEEE Transactions on Pattern Analysis and Machine Intelligence,46(12):1-14.
[9]QYY.Exploring the Untouched Sweeps for Conflict-Aware 3D Segmentation Pretraining.arXiv,2024,
[10]QYY.Mutual Information Guided Optimal Transport for Unsupervised Visible-Infrared Person Re-identification.arXiv,2024,
total233 1/24
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