no code implementations • 16 Dec 2024 • Kaixuan Wang, Lin Qi, Shiyu Qin, Kai Luo, Yakun Ju, Xia Li, Junyu Dong
Photometric stereo (PS) endeavors to ascertain surface normals using shading clues from photometric images under various illuminations.
1 code implementation • 11 Apr 2024 • Kai Luo, Yakun Ju, Lin Qi, Kaixuan Wang, Junyu Dong
Predicting accurate normal maps of objects from two-dimensional images in regions of complex structure and spatial material variations is challenging using photometric stereo methods due to the influence of surface reflection properties caused by variations in object geometry and surface materials.
1 code implementation • Under review for Transaction 2024 • Mu Hu, Wei Yin, Chi Zhang, Zhipeng Cai, Xiaoxiao Long, Kaixuan Wang, Hao Chen, Gang Yu, Chunhua Shen, Shaojie Shen
For metric depth estimation, we show that the key to a zero-shot single-view model lies in resolving the metric ambiguity from various camera models and large-scale data training.
Ranked #1 on
Surface Normals Estimation
on NYU Depth v2
(using extra training data)
1 code implementation • 18 Mar 2024 • Xiao Fu, Wei Yin, Mu Hu, Kaixuan Wang, Yuexin Ma, Ping Tan, Shaojie Shen, Dahua Lin, Xiaoxiao Long
We introduce GeoWizard, a new generative foundation model designed for estimating geometric attributes, e. g., depth and normals, from single images.
1 code implementation • CVPR 2024 • Junda Cheng, Wei Yin, Kaixuan Wang, Xiaozhi Chen, Shijie Wang, Xin Yang
In this work, we propose a new robustness benchmark to evaluate the depth estimation system under various noisy pose settings.
Ranked #1 on
Monocular Depth Estimation
on DDAD
1 code implementation • 16 Feb 2024 • Xuelun Shen, Zhipeng Cai, Wei Yin, Matthias Müller, Zijun Li, Kaixuan Wang, Xiaozhi Chen, Cheng Wang
Given an architecture, GIM first trains it on standard domain-specific datasets and then combines it with complementary matching methods to create dense labels on nearby frames of novel videos.
Ranked #1 on
Pose Estimation
on InLoc
2 code implementations • 18 Jan 2024 • Zhongliang Guo, Junhao Dong, Yifei Qian, Kaixuan Wang, Weiye Li, Ziheng Guo, Yuheng Wang, Yanli Li, Ognjen Arandjelović, Lei Fang
Neural style transfer (NST) generates new images by combining the style of one image with the content of another.
no code implementations • 28 Nov 2023 • Kai Cheng, Xiaoxiao Long, Wei Yin, Jin Wang, Zhiqiang Wu, Yuexin Ma, Kaixuan Wang, Xiaozhi Chen, Xuejin Chen
Multi-camera setups find widespread use across various applications, such as autonomous driving, as they greatly expand sensing capabilities.
1 code implementation • ICCV 2023 • Wei Yin, Chi Zhang, Hao Chen, Zhipeng Cai, Gang Yu, Kaixuan Wang, Xiaozhi Chen, Chunhua Shen
State-of-the-art (SOTA) monocular metric depth estimation methods can only handle a single camera model and are unable to perform mixed-data training due to the metric ambiguity.
Ranked #26 on
Monocular Depth Estimation
on NYU-Depth V2
(using extra training data)
no code implementations • 11 Jul 2023 • Chunxi Guo, Zhiliang Tian, Jintao Tang, Shasha Li, Zhihua Wen, Kaixuan Wang, Ting Wang
Prompt learning with large language models (LLMs) has emerged as a recent approach, which designs prompts to lead LLMs to understand the input question and generate the corresponding SQL.
1 code implementation • CVPR 2023 • Rui Li, Dong Gong, Wei Yin, Hao Chen, Yu Zhu, Kaixuan Wang, Xiaozhi Chen, Jinqiu Sun, Yanning Zhang
To let the geometric perception learned from multi-view cues in static areas propagate to the monocular representation in dynamic areas and let monocular cues enhance the representation of multi-view cost volume, we propose a cross-cue fusion (CCF) module, which includes the cross-cue attention (CCA) to encode the spatially non-local relative intra-relations from each source to enhance the representation of the other.
no code implementations • 14 Apr 2023 • Jaime Spencer, C. Stella Qian, Michaela Trescakova, Chris Russell, Simon Hadfield, Erich W. Graf, Wendy J. Adams, Andrew J. Schofield, James Elder, Richard Bowden, Ali Anwar, Hao Chen, Xiaozhi Chen, Kai Cheng, Yuchao Dai, Huynh Thai Hoa, Sadat Hossain, Jianmian Huang, Mohan Jing, Bo Li, Chao Li, Baojun Li, Zhiwen Liu, Stefano Mattoccia, Siegfried Mercelis, Myungwoo Nam, Matteo Poggi, Xiaohua Qi, Jiahui Ren, Yang Tang, Fabio Tosi, Linh Trinh, S. M. Nadim Uddin, Khan Muhammad Umair, Kaixuan Wang, YuFei Wang, Yixing Wang, Mochu Xiang, Guangkai Xu, Wei Yin, Jun Yu, Qi Zhang, Chaoqiang Zhao
This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC).
no code implementations • 5 Oct 2022 • Jialei Xu, Xianming Liu, Yuanchao Bai, Junjun Jiang, Kaixuan Wang, Xiaozhi Chen, Xiangyang Ji
During the iterative update, the results of depth estimation are compared across cameras and the information of overlapping areas is propagated to the whole depth maps with the help of basis formulation.
no code implementations • 26 Sep 2021 • Wenwei Liu, Hui Feng, Kaixuan Wang, Feng Ji, Bo Hu
Sampling and interpolation have been extensively studied, in order to reconstruct or estimate the entire graph signal from the signal values on a subset of vertexes, of which most achievements are about continuous signals.
1 code implementation • 12 Sep 2019 • Kaixuan Wang, Shaojie Shen
Third, beyond two-view depth estimation, we further extend the above networks to fuse depth information from multiple target images and estimate the depth map of the source image.
1 code implementation • 10 Sep 2019 • Kaixuan Wang, Fei Gao, Shaojie Shen
First, superpixels extracted from both intensity and depth images are used to model surfels in the system.
no code implementations • 24 Jun 2019 • Wenchao Ding, Wenliang Gao, Kaixuan Wang, Shaojie Shen
Our framework starts with an efficient B-spline-based kinodynamic (EBK) search algorithm which finds a feasible trajectory with minimum control effort and time.
no code implementations • 26 Mar 2019 • Yonggen Ling, Kaixuan Wang, Shaojie Shen
This paper presents a probabilistic approach for online dense reconstruction using a single monocular camera moving through the environment.
Robotics
1 code implementation • 23 Jul 2018 • Kaixuan Wang, Shaojie Shen
In this paper, we present MVDepthNet, a convolutional network to solve the depth estimation problem given several image-pose pairs from a localized monocular camera in neighbor viewpoints.