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Superpixel Transformers for Efficient Semantic Segmentation., , , , , , и . IROS, стр. 7651-7658. (2023)FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning., , , , , , и . Trans. Mach. Learn. Res., (2024)FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning., , , , , , и . CoRR, (2023)Are Transformers more robust than CNNs?, , , и . NeurIPS, стр. 26831-26843. (2021)Shape-Texture Debiased Neural Network Training., , , , , , , и . ICLR, OpenReview.net, (2021)Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning., , , , и . ICLR, OpenReview.net, (2024)A Semantic Space is Worth 256 Language Descriptions: Make Stronger Segmentation Models with Descriptive Properties., , , , , , , , , и . ECCV (38), том 15096 из Lecture Notes in Computer Science, стр. 239-258. Springer, (2024)Fast AdvProp., , , , , , , и . ICLR, OpenReview.net, (2022)Waymo Open Dataset: Panoramic Video Panoptic Segmentation., , , , , , и . ECCV (29), том 13689 из Lecture Notes in Computer Science, стр. 53-72. Springer, (2022)In Defense of Image Pre-Training for Spatiotemporal Recognition., , , , , , и . ECCV (25), том 13685 из Lecture Notes in Computer Science, стр. 675-691. Springer, (2022)