Zero volume boundary for extension domains from Sobolev to $BV$

Kavli Affiliate: Zheng Zhu | First 5 Authors: Tapio Rajala, Zheng Zhu, , , | Summary: In this note, we prove that the boundary of a $(W^{1, p}, BV)$-extension domain is of volume zero under the assumption that the domain $boz$ is $1$-fat at almost every $xinpartialboz$. Especially, the boundary of any planar $(W^{1, p}, […]


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BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

Kavli Affiliate: Zheng Zhu | First 5 Authors: Yunpeng Zhang, Zheng Zhu, Wenzhao Zheng, Junjie Huang, Guan Huang | Summary: In this paper, we present BEVerse, a unified framework for 3D perception and prediction based on multi-camera systems. Unlike existing studies focusing on the improvement of single-task approaches, BEVerse features in producing spatio-temporal Birds-Eye-View (BEV) […]


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Discrete time crystals enforced by Floquet-Bloch scars

Kavli Affiliate: Biao Huang | First 5 Authors: Biao Huang, Tsz-Him Leung, Dan Stamper-Kurn, W. Vincent Liu, | Summary: We analytically identify a new class of quantum scars protected by spatiotemporal translation symmetries, dubbed Floquet-Bloch scars. They distinguish from previous (quasi-)static scars by a rigid spectral pairing only possible in Floquet systems, where strong interaction […]


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Plasma Image Classification Using Cosine Similarity Constrained CNN

Kavli Affiliate: Yi Zhou | First 5 Authors: Michael J. Falato, Bradley T. Wolfe, Tali M. Natan, Xinhua Zhang, Ryan S. Marshall | Summary: Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei, and young stellar objects commonly emit plasma jets in various […]


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Introspective Deep Metric Learning

Kavli Affiliate: Zheng Zhu | First 5 Authors: Chengkun Wang, Wenzhao Zheng, Zheng Zhu, Jie Zhou, Jiwen Lu | Summary: This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images. Conventional deep metric learning methods produce confident semantic distances between images regardless of the uncertainty level. However, we argue that […]


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Gait Recognition in the Wild: A Benchmark

Kavli Affiliate: Zheng Zhu | First 5 Authors: Zheng Zhu, Xianda Guo, Tian Yang, Junjie Huang, Jiankang Deng | Summary: Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognition, academia is restricted by current existing databases captured in the controlled […]


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Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline

Kavli Affiliate: Zheng Zhu | First 5 Authors: Xianda Guo, Zheng Zhu, Tian Yang, Beibei Lin, Junjie Huang | Summary: Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognition, academia is restricted by current existing databases captured in the controlled […]


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Half-Wormholes and Ensemble Averages

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Jia Tian, Yingyu Yang, , | Summary: We study "half-wormhole-like" saddle point contributions to spectral correlators in a variety of ensemble average models, including various statistical models, generalized 0d SYK models, 1d Brownian SYK models and an extension of it. In statistical ensemble models, where […]


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DDDM: a Brain-Inspired Framework for Robust Classification

Kavli Affiliate: Yi Zhou | First 5 Authors: Xiyuan Chen, Xingyu Li, Yi Zhou, Tianming Yang, | Summary: Despite their outstanding performance in a broad spectrum of real-world tasks, deep artificial neural networks are sensitive to input noises, particularly adversarial perturbations. On the contrary, human and animal brains are much less vulnerable. In contrast to […]


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SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities

Kavli Affiliate: Yi Zhou | First 5 Authors: Pengbo Hu, Xingyu Li, Yi Zhou, , | Summary: As deep learning advances, there is an ever-growing demand for models capable of synthesizing information from multi-modal resources to address the complex tasks raised from real-life applications. Recently, many large multi-modal datasets have been collected, on which researchers […]


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