1 code implementation • 22 Jul 2024 • Jia Shi, Gautam Gare, Jinjin Tian, Siqi Chai, Zhiqiu Lin, Arun Vasudevan, Di Feng, Francesco Ferroni, Shu Kong
We assess 75 models using ImageNet as the ID dataset and five significantly shifted OOD variants, uncovering a strong linear correlation between ID LCA distance and OOD top-1 accuracy.
no code implementations • 21 Jun 2022 • Chenguang Li, Jia Shi, Ya Wang, Guangliang Cheng
Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global.
no code implementations • 21 Jun 2022 • Chenguang Li, Boheng Zhang, Jia Shi, Guangliang Cheng
We focus on bridging domain discrepancy in lane detection among different scenarios to greatly reduce extra annotation and re-training costs for autonomous driving.
no code implementations • CVPR 2022 • Chenguang Li, Jia Shi, Ya Wang, Guangliang Cheng
Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global.
Ranked #7 on
3D Lane Detection
on Apollo Synthetic 3D Lane
no code implementations • 19 May 2022 • Zhengqin Li, Jia Shi, Sai Bi, Rui Zhu, Kalyan Sunkavalli, Miloš Hašan, Zexiang Xu, Ravi Ramamoorthi, Manmohan Chandraker
We tackle this problem using two novel components: 1) a holistic scene reconstruction method that estimates scene reflectance and parametric 3D lighting, and 2) a neural rendering framework that re-renders the scene from our predictions.
1 code implementation • 17 Jan 2022 • Zhiqiu Lin, Jia Shi, Deepak Pathak, Deva Ramanan
The major strength of CLEAR over prior CL benchmarks is the smooth temporal evolution of visual concepts with real-world imagery, including both high-quality labeled data along with abundant unlabeled samples per time period for continual semi-supervised learning.
no code implementations • 9 Jan 2022 • Long Yang, Jiangtao Wang, Xuan Xue, Jia Shi, Yongchao Wang
In this paper, we investigate the secure beamforming design in an intelligent reflection surface (IRS) assisted millimeter wave (mmWave) system, where the hybrid beamforming (HB) and the passive beamforming (PB) are employed by the transmitter and the IRS, respectively.
no code implementations • CVPR 2021 • Zhengqin Li, Ting-Wei Yu, Shen Sang, Sarah Wang, Meng Song, YuHan Liu, Yu-Ying Yeh, Rui Zhu, Nitesh Gundavarapu, Jia Shi, Sai Bi, Hong-Xing Yu, Zexiang Xu, Kalyan Sunkavalli, Milos Hasan, Ravi Ramamoorthi, Manmohan Chandraker
Finally, we demonstrate that our framework may also be integrated with physics engines, to create virtual robotics environments with unique ground truth such as friction coefficients and correspondence to real scenes.
no code implementations • 8 Dec 2020 • Javier Gómez-Serrano, Jaemin Park, Jia Shi, Yao Yao
In this paper, we show that the only solution of the vortex sheet equation, either stationary or uniformly rotating with negative angular velocity $\Omega$, such that it has positive vorticity and is concentrated in a finite disjoint union of smooth curves with finite length is the trivial one: constant vorticity amplitude supported on a union of nested, concentric circles.
Analysis of PDEs
no code implementations • 25 Jul 2020 • Zhengqin Li, Ting-Wei Yu, Shen Sang, Sarah Wang, Meng Song, YuHan Liu, Yu-Ying Yeh, Rui Zhu, Nitesh Gundavarapu, Jia Shi, Sai Bi, Zexiang Xu, Hong-Xing Yu, Kalyan Sunkavalli, Miloš Hašan, Ravi Ramamoorthi, Manmohan Chandraker
Finally, we demonstrate that our framework may also be integrated with physics engines, to create virtual robotics environments with unique ground truth such as friction coefficients and correspondence to real scenes.
2 code implementations • 25 Jun 2019 • Jia Shi, Ruipeng Li, Yuanzhe Xi, Yousef Saad, Maarten V. de Hoop
A Continuous Galerkin method-based approach is presented to compute the seismic normal modes of rotating planets.
Computational Physics Earth and Planetary Astrophysics Geophysics 86-08, 86-04, 85-04, 85-08, 85-10, 15A18, 65N25, 65N30