no code implementations • 11 Nov 2024 • Yiwen Duan, Yonghong Yu, Xiaoming Zhao, Yichang Wu, Wenbo Liu
Code Large Language Models (Code LLMs), such as Code llama and DeepSeek-Coder, have demonstrated exceptional performance in the code generation tasks.
1 code implementation • CVPR 2024 • Zhenggang Tang, Zhongzheng Ren, Xiaoming Zhao, Bowen Wen, Jonathan Tremblay, Stan Birchfield, Alexander Schwing
We present a method for automatically modifying a NeRF representation based on a single observation of a non-rigid transformed version of the original scene.
no code implementations • 10 Jun 2024 • Xiaoming Zhao, Pratul P. Srinivasan, Dor Verbin, Keunhong Park, Ricardo Martin Brualla, Philipp Henzler
Existing methods for relightable view synthesis -- using a set of images of an object under unknown lighting to recover a 3D representation that can be rendered from novel viewpoints under a target illumination -- are based on inverse rendering, and attempt to disentangle the object geometry, materials, and lighting that explain the input images.
1 code implementation • 1 Jun 2024 • Jinyin Chen, Xiaoming Zhao, Haibin Zheng, Xiao Li, Sheng Xiang, Haifeng Guo
Knowledge distillation (KD) is one of the widely used compression techniques for edge deployment, by obtaining a lightweight student model from a well-trained teacher model released on public platforms.
1 code implementation • CVPR 2024 • Jing Wen, Xiaoming Zhao, Zhongzheng Ren, Alexander G. Schwing, Shenlong Wang
We introduce GoMAvatar, a novel approach for real-time, memory-efficient, high-quality animatable human modeling.
no code implementations • 12 Oct 2023 • Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Angel Bautista, Joshua M. Susskind, Alexander G. Schwing
In contrast, for dynamic scenes, scene-specific optimization techniques exist, but, to our best knowledge, there is currently no generalized method for dynamic novel view synthesis from a given monocular video.
2 code implementations • 7 Apr 2023 • Xiaoming Zhao, Xingming Wu, Weihai Chen, Peter C. Y. Chen, Qingsong Xu, Zhengguo Li
Image keypoints and descriptors play a crucial role in many visual measurement tasks.
1 code implementation • 4 Aug 2022 • Xiaoming Zhao, Yuan-Ting Hu, Zhongzheng Ren, Alexander G. Schwing
Specifically, a set of 3D locations within the view-frustum of the camera are first projected independently onto the image and a corresponding feature is subsequently extracted for each 3D location.
no code implementations • 28 Jul 2022 • Xiaoming Zhao, Zhizhen Zhao, Alexander G. Schwing
While recovery of geometry from image and video data has received a lot of attention in computer vision, methods to capture the texture for a given geometry are less mature.
1 code implementation • 21 Jul 2022 • Xiaoming Zhao, Fangchang Ma, David Güera, Zhile Ren, Alexander G. Schwing, Alex Colburn
What is really needed to make an existing 2D GAN 3D-aware?
no code implementations • 31 Dec 2021 • Xiaoming Zhao, Weihai Chen, Xingming Wu, Peter C. Y. Chen, Zhengguo Li
Deep stereo matching has made significant progress in recent years.
2 code implementations • 6 Dec 2021 • Xiaoming Zhao, Xingming Wu, Jinyu Miao, Weihai Chen, Peter C. Y. Chen, Zhengguo Li
The reprojection loss is then proposed to directly optimize these sub-pixel keypoints, and the dispersity peak loss is presented for accurate keypoints regularization.
no code implementations • NeurIPS 2021 • Zhongzheng Ren, Xiaoming Zhao, Alexander G. Schwing
We introduce REDO, a class-agnostic framework to REconstruct the Dynamic Objects from RGBD or calibrated videos.
no code implementations • 17 Nov 2021 • Xiaoming Zhao, Jingmeng Liu, Xingming Wu, Weihai Chen, Fanghong Guo, Zhengguo Li
Keypoints matching is a pivotal component for many image-relevant applications such as image stitching, visual simultaneous localization and mapping (SLAM), and so on.
no code implementations • ICCV 2021 • Xiaoming Zhao, Harsh Agrawal, Dhruv Batra, Alexander Schwing
It is fundamental for personal robots to reliably navigate to a specified goal.
no code implementations • 20 May 2019 • Wei-Ye Zhao, Xi-Ya Guan, Yang Liu, Xiaoming Zhao, Jian Peng
Recent advances in deep reinforcement learning have achieved human-level performance on a variety of real-world applications.