Modeling Ride-Sourcing Matching and Pickup Processes based on Additive Gaussian Process Models

Kavli Affiliate: Zheng Zhu | First 5 Authors: Zheng Zhu, Meng Xu, Yining Di, Xiqun Chen, Jingru Yu | Summary: Matching and pickup processes are core features of ride-sourcing services. Previous studies have adopted abundant analytical models to depict the two processes and obtain operational insights; while the goodness of fit between models and data […]


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Model predictive control of agro-hydrological systems based on a two-layer neural network modeling framework

Kavli Affiliate: Biao Huang | First 5 Authors: Zhiyinan Huang, Jinfeng Liu, Biao Huang, , | Summary: Water scarcity is an urgent issue to be resolved and improving irrigation water-use efficiency through closed-loop control is essential. The complex agro-hydrological system dynamics, however, often pose challenges in closed-loop control applications. In this work, we propose a […]


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WebFace260M: A Benchmark for Million-Scale Deep Face Recognition

Kavli Affiliate: Zheng Zhu | First 5 Authors: Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, Junjie Huang | Summary: Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchmark, containing uncurated 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces […]


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MVSTER: Epipolar Transformer for Efficient Multi-View Stereo

Kavli Affiliate: Zheng Zhu | First 5 Authors: Xiaofeng Wang, Zheng Zhu, Fangbo Qin, Yun Ye, Guan Huang | Summary: Learning-based Multi-View Stereo (MVS) methods warp source images into the reference camera frustum to form 3D volumes, which are fused as a cost volume to be regularized by subsequent networks. The fusing step plays a […]


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Matrix Entanglement

Kavli Affiliate: Cheng Peng | First 5 Authors: Vaibhav Gautam, Masanori Hanada, Antal Jevicki, Cheng Peng, | Summary: In gauge/gravity duality, matrix degrees of freedom on the gauge theory side play important roles for the emergent geometry. In this paper, we discuss how the entanglement on the gravity side can be described as the entanglement […]


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HFT: Lifting Perspective Representations via Hybrid Feature Transformation

Kavli Affiliate: Zheng Zhu | First 5 Authors: Jiayu Zou, Junrui Xiao, Zheng Zhu, Junjie Huang, Guan Huang | Summary: Autonomous driving requires accurate and detailed Bird’s Eye View (BEV) semantic segmentation for decision making, which is one of the most challenging tasks for high-level scene perception. Feature transformation from frontal view to BEV is […]


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Interplay between Pair Density Wave and a Nested Fermi Surface

Kavli Affiliate: Yi Zhou | First 5 Authors: Jin-Tao Jin, Kun Jiang, Hong Yao, Yi Zhou, | Summary: We show that spontaneous time-reversal-symmetry (TRS) breaking can naturally arise from the interplay between pair density wave (PDW) ordering at multiple momenta and nesting of Fermi surfaces (FS). Concretely, we consider pair-density-wave superconductivity on a hexagonal lattice […]


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SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation

Kavli Affiliate: Zheng Zhu | First 5 Authors: Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Yongming Rao | Summary: Depth estimation from images serves as the fundamental step of 3D perception for autonomous driving and is an economical alternative to expensive depth sensors like LiDAR. The temporal photometric consistency enables self-supervised depth estimation without […]


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SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation

Kavli Affiliate: Zheng Zhu | First 5 Authors: Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Yongming Rao | Summary: Depth estimation from images serves as the fundamental step of 3D perception for autonomous driving and is an economical alternative to expensive depth sensors like LiDAR. The temporal photometric constraints enables self-supervised depth estimation without […]


Continue.. SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation