6 code implementations • ICCV 2017 • Zili Yi, Hao Zhang, Ping Tan, Minglun Gong
Depending on the task complexity, thousands to millions of labeled image pairs are needed to train a conditional GAN.
Ranked #2 on Image-to-Image Translation on Aerial-to-Map
1 code implementation • 30 Jul 2020 • Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, Li Cheng
Action recognition is a relatively established task, where givenan input sequence of human motion, the goal is to predict its ac-tion category.
1 code implementation • NeurIPS 2019 • Chunjin Song, Zhijie Wu, Yang Zhou, Minglun Gong, Hui Huang
Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al.
1 code implementation • 15 Jul 2021 • Xinxin Zuo, Sen Wang, Qiang Sun, Minglun Gong, Li Cheng
However, Chamfer distance is quite sensitive to noise and outliers, thus could be unreliable to assign correspondences.
1 code implementation • ICCV 2021 • Shihao Zou, Chuan Guo, Xinxin Zuo, Sen Wang, Pengyu Wang, Xiaoqin Hu, Shoushun Chen, Minglun Gong, Li Cheng
Event camera is an emerging imaging sensor for capturing dynamics of moving objects as events, which motivates our work in estimating 3D human pose and shape from the event signals.
2 code implementations • 22 Mar 2018 • Zili Yi, Zhiqin Chen, Hao Cai, Wendong Mao, Minglun Gong, Hao Zhang
The key feature of BSD-GAN is that it is trained in multiple branches, progressively covering both the breadth and depth of the network, as resolutions of the training images increase to reveal finer-scale features.
no code implementations • 9 May 2018 • Bojian Wu, Yang Zhou, Yiming Qian, Minglun Gong, Hui Huang
Numerous techniques have been proposed for reconstructing 3D models for opaque objects in past decades.
no code implementations • 2 Oct 2018 • Mingjie Wang, Jun Zhou, Wendong Mao, Minglun Gong
To address this problem, a regularization method named Stochastic Feature Reuse is also presented.
no code implementations • 2 Oct 2018 • Wendong Mao, Mingjie Wang, Jun Zhou, Minglun Gong
A robust solution for semi-dense stereo matching is presented.
no code implementations • 26 Nov 2018 • Zhijie Wu, Chunjin Song, Yang Zhou, Minglun Gong, Hui Huang
Style transfer has been an important topic both in computer vision and graphics.
no code implementations • ECCV 2018 • Yiming Qian, Yinqiang Zheng, Minglun Gong, Yee-Hong Yang
This paper presents the first approach for simultaneously recovering the 3D shape of both the wavy water surface and the moving underwater scene.
no code implementations • CVPR 2013 • Timothy Yau, Minglun Gong, Yee-Hong Yang
In underwater imagery, the image formation process includes refractions that occur when light passes from water into the camera housing, typically through a flat glass port.
no code implementations • CVPR 2016 • Yiming Qian, Minglun Gong, Yee Hong Yang
Estimating the shape of transparent and refractive objects is one of the few open problems in 3D reconstruction.
no code implementations • CVPR 2017 • Yiming Qian, Minglun Gong, Yee-Hong Yang
3D reconstruction of dynamic fluid surfaces is an open and challenging problem in computer vision.
no code implementations • ICCV 2015 • Yiming Qian, Minglun Gong, Yee-Hong Yang
Extracting environment mattes using existing approaches often requires either thousands of captured images or a long processing time, or both.
no code implementations • 30 Apr 2020 • Shihao Zou, Xinxin Zuo, Yiming Qian, Sen Wang, Chuan Guo, Chi Xu, Minglun Gong, Li Cheng
Polarization images are known to be able to capture polarized reflected lights that preserve rich geometric cues of an object, which has motivated its recent applications in reconstructing detailed surface normal of the objects of interest.
no code implementations • 25 May 2020 • Mingjie Wang, Hao Cai, Jun Zhou, Minglun Gong
Crowd counting is an important vision task, which faces challenges on continuous scale variation within a given scene and huge density shift both within and across images.
no code implementations • 5 Jun 2020 • Xinxin Zuo, Sen Wang, Jiangbin Zheng, Weiwei Yu, Minglun Gong, Ruigang Yang, Li Cheng
First, based on a generative human template, for every two frames having sufficient overlap, an initial pairwise alignment is performed; It is followed by a global non-rigid registration procedure, in which partial results from RGBD frames are collected into a unified 3D shape, under the guidance of correspondences from the pairwise alignment; Finally, the texture map of the reconstructed human model is optimized to deliver a clear and spatially consistent texture.
no code implementations • ECCV 2020 • Shihao Zou, Xinxin Zuo, Yiming Qian, Sen Wang, Chi Xu, Minglun Gong, Li Cheng
Inspired by the recent advances in human shape estimation from single color images, in this paper, we attempt at estimating human body shapes by leveraging the geometric cues from single polarization images.
no code implementations • 3 Sep 2020 • Ruizhen Hu, Juzhan Xu, Bin Chen, Minglun Gong, Hao Zhang, Hui Huang
Using a learning-based approach, a trained network can learn and encode solution patterns to guide the solution of new problem instances instead of executing an expensive online search.
no code implementations • 18 Dec 2020 • Mingjie Wang, Hao Cai, XianFeng Han, Jun Zhou, Minglun Gong
To battle the ingrained issue of accuracy degradation, we propose a novel and powerful network called Scale Tree Network (STNet) for accurate crowd counting.
no code implementations • 5 Aug 2021 • Ji Yang, Xinxin Zuo, Sen Wang, Zhenbo Yu, Xingyu Li, Bingbing Ni, Minglun Gong, Li Cheng
A dataset of generic 3D objects with ground-truth annotated skeletons is collected.
no code implementations • 12 Nov 2021 • Chuan Guo, Xinxin Zuo, Sen Wang, Xinshuang Liu, Shihao Zou, Minglun Gong, Li Cheng
Action2motion stochastically generates plausible 3D pose sequences of a prescribed action category, which are processed and rendered by motion2video to form 2D videos.
no code implementations • 26 Nov 2021 • Ji Yang, Youdong Ma, Xinxin Zuo, Sen Wang, Minglun Gong, Li Cheng
This paper considers to jointly tackle the highly correlated tasks of estimating 3D human body poses and predicting future 3D motions from RGB image sequences.
no code implementations • 15 Mar 2022 • Mingjie Wang, Jun Zhou, Hao Cai, Minglun Gong
Existing state-of-the-art crowd counting algorithms rely excessively on location-level annotations, which are burdensome to acquire.
no code implementations • 10 Feb 2023 • Mingjie Wang, Yande Li, Jun Zhou, Graham W. Taylor, Minglun Gong
The class-agnostic counting (CAC) problem has caught increasing attention recently due to its wide societal applications and arduous challenges.
no code implementations • 14 Feb 2023 • Zhentao Huang, Yukun Shi, Minglun Gong
The performance of PatchMatch-based multi-view stereo algorithms depends heavily on the source views selected for computing matching costs.
no code implementations • 23 Mar 2023 • Yande Li, Mingjie Wang, Minglun Gong, Yonggang Lu, Li Liu
The ever-increasing demands for intuitive interactions in Virtual Reality has triggered a boom in the realm of Facial Expression Recognition (FER).
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 24 Apr 2023 • Wanglong Lu, Xianta Jiang, Xiaogang Jin, Yong-Liang Yang, Minglun Gong, Tao Wang, Kaijie Shi, Hanli Zhao
Image inpainting is the task of filling in missing or masked region of an image with semantically meaningful contents.
no code implementations • 17 Oct 2023 • Juzhan Xu, Minglun Gong, Hao Zhang, Hui Huang, Ruizhen Hu
We present a novel learning framework to solve the transport-and-packing (TAP) problem in 3D.
no code implementations • 8 Feb 2024 • Mingjie Wang, Jun Zhou, Yong Dai, Eric Buys, Minglun Gong
Recently, Class-Agnostic Counting (CAC) problem has garnered increasing attention owing to its intriguing generality and superior efficiency compared to Category-Specific Counting (CSC).
no code implementations • 21 Feb 2024 • Zhentao Huang, Yukun Shi, Neil Bruce, Minglun Gong
The widespread adoption of implicit neural representations, especially Neural Radiance Fields (NeRF), highlights a growing need for editing capabilities in implicit 3D models, essential for tasks like scene post-processing and 3D content creation.