1 code implementation • CVPR 2024 • Sizhe Li, Yiming Qin, Minghang Zheng, Xin Jin, Yang Liu
When editing a video, a piece of attractive background music is indispensable.
1 code implementation • CVPR 2024 • David Charatan, Sizhe Li, Andrea Tagliasacchi, Vincent Sitzmann
We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images.
Ranked #2 on
Generalizable Novel View Synthesis
on ACID
no code implementations • 28 Nov 2023 • Hao Pei, Si Lin, Chuanfu Li, Che Wang, Haoming Chen, Sizhe Li
To enhance the intelligence degree in operation and maintenance, a novel method for fault detection in power grids is proposed.
no code implementations • 22 Nov 2023 • Weiwei Li, Xing Liu, Wei Wang, Lu Chen, Sizhe Li, Hui Fan
To address the challenge of identifying hidden danger in substations from unstructured text, a novel dynamic analysis method is proposed.
no code implementations • 15 Nov 2023 • Xiang Li, Che Wang, Bing Li, Hao Chen, Sizhe Li
In this paper, we propose a method for knowledge graph construction in power distribution networks.
no code implementations • 14 Nov 2023 • Wenxi Zhang, Zhe Li, Weixi Li, Weisi Ma, Xinyi Chen, Sizhe Li
This paper introduces a robust, learning-based method for diagnosing the state of distribution network switchgear, which is crucial for maintaining the power quality for end users.
no code implementations • 6 Nov 2023 • Siyi Zhang, Cheng Liu, Xiang Li, Xin Zhai, Zhen Wei, Sizhe Li, Xun Ma
The current trend of automating inspections at substations has sparked a surge in interest in the field of transformer image recognition.
no code implementations • 3 Nov 2023 • Weiying Lin, Che Liu, Xin Zhang, Zhen Wei, Sizhe Li, Xun Ma
The process begins with histogram equalization to enhance the original image, followed by the use of Mask RCNN to identify the preliminary positions and outlines of oil tanks, the ground, and areas of potential oil contamination.
no code implementations • 2 Nov 2023 • Weixi Wang, Xichen Zhong, Xin Li, Sizhe Li, Xun Ma
Overhead line inspection greatly benefits from defect recognition using visible light imagery.
no code implementations • 30 Oct 2023 • Sizhe Li, Xun Ma, Nan Liu, Yi Jin
Transmission line state assessment and prediction are of great significance for the rational formulation of operation and maintenance strategy and improvement of operation and maintenance level.
no code implementations • 27 Mar 2023 • Sizhe Li, Zhiao Huang, Tao Chen, Tao Du, Hao Su, Joshua B. Tenenbaum, Chuang Gan
Reinforcement learning approaches for dexterous rigid object manipulation would struggle in this setting due to the complexity of physics interaction with deformable objects.
no code implementations • ICLR 2022 • Sizhe Li, Zhiao Huang, Tao Du, Hao Su, Joshua B. Tenenbaum, Chuang Gan
Extensive experimental results suggest that: 1) on multi-stage tasks that are infeasible for the vanilla differentiable physics solver, our approach discovers contact points that efficiently guide the solver to completion; 2) on tasks where the vanilla solver performs sub-optimally or near-optimally, our contact point discovery method performs better than or on par with the manipulation performance obtained with handcrafted contact points.
no code implementations • 10 Nov 2021 • Sizhe Li, Yapeng Tian, Chenliang Xu
Leveraging temporal synchronization and association within sight and sound is an essential step towards robust localization of sounding objects.
1 code implementation • 1 Aug 2020 • Jing Shi, Zhiheng Li, Haitian Zheng, Yihang Xu, Tianyou Xiao, Weitao Tan, Xiaoning Guo, Sizhe Li, Bin Yang, Zhexin Xu, Ruitao Lin, Zhongkai Shangguan, Yue Zhao, Jingwen Wang, Rohan Sharma, Surya Iyer, Ajinkya Deshmukh, Raunak Mahalik, Srishti Singh, Jayant G Rohra, Yi-Peng Zhang, Tongyu Yang, Xuan Wen, Ethan Fahnestock, Bryce Ikeda, Ian Lawson, Alan Finkelstein, Kehao Guo, Richard Magnotti, Andrew Sexton, Jeet Ketan Thaker, Yiyang Su, Chenliang Xu
This technical report summarizes submissions and compiles from Actor-Action video classification challenge held as a final project in CSC 249/449 Machine Vision course (Spring 2020) at University of Rochester