no code implementations • 28 Mar 2024 • BoWen Zhang, Yiji Cheng, Jiaolong Yang, Chunyu Wang, Feng Zhao, Yansong Tang, Dong Chen, Baining Guo
To address the problem, we introduce GaussianCube, a structured GS representation that is both powerful and efficient for generative modeling.
1 code implementation • 23 Jan 2024 • Fei Xie, Wankou Yang, Chunyu Wang, Lei Chu, Yue Cao, Chao Ma, Wenjun Zeng
Thus, we reformulate the two-branch Siamese tracking as a conceptually simple, fully transformer-based Single-Branch Tracking pipeline, dubbed SBT.
no code implementations • 22 Dec 2023 • Jinpeng Liu, Wenxun Dai, Chunyu Wang, Yiji Cheng, Yansong Tang, Xin Tong
Some works use the CLIP model to align the motion space and the text space, aiming to enable motion generation from natural language motion descriptions.
1 code implementation • 18 Dec 2023 • Zhicong Tang, Shuyang Gu, Chunyu Wang, Ting Zhang, Jianmin Bao, Dong Chen, Baining Guo
The 3D volumes are then trained on a diffusion model for text-to-3D generation using a 3D U-Net.
no code implementations • 30 Nov 2023 • Yanhui Wang, Jianmin Bao, Wenming Weng, Ruoyu Feng, Dacheng Yin, Tao Yang, Jingxu Zhang, Qi Dai Zhiyuan Zhao, Chunyu Wang, Kai Qiu, Yuhui Yuan, Chuanxin Tang, Xiaoyan Sun, Chong Luo, Baining Guo
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation.
no code implementations • 30 Nov 2023 • Wenming Weng, Ruoyu Feng, Yanhui Wang, Qi Dai, Chunyu Wang, Dacheng Yin, Zhiyuan Zhao, Kai Qiu, Jianmin Bao, Yuhui Yuan, Chong Luo, Yueyi Zhang, Zhiwei Xiong
Second, it preserves the high-fidelity generation ability of the pre-trained image diffusion models by making only minimal network modifications.
no code implementations • 26 Nov 2023 • Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, Han Hu, HsiangTao Wu, Sheng Zhao, Jiang Bian
Zero-shot talking avatar generation aims at synthesizing natural talking videos from speech and a single portrait image.
no code implementations • 18 Nov 2023 • Ziwei Liao, Jialiang Zhu, Chunyu Wang, Han Hu, Steven L. Waslander
In this work, we aim to improve the 3D reasoning ability of Transformers in multi-view 3D human pose estimation.
1 code implementation • 8 Aug 2023 • Yichao Shen, Zigang Geng, Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, Baining Guo
We introduce a highly performant 3D object detector for point clouds using the DETR framework.
Ranked #2 on 3D Object Detection on ScanNetV2
1 code implementation • CVPR 2023 • Zigang Geng, Chunyu Wang, Yixuan Wei, Ze Liu, Houqiang Li, Han Hu
Human pose is typically represented by a coordinate vector of body joints or their heatmap embeddings.
Ranked #1 on Pose Estimation on MPII Human Pose
1 code implementation • CVPR 2023 • Xiaoxuan Ma, Jiajun Su, Chunyu Wang, Wentao Zhu, Yizhou Wang
The advanced motion capture systems solve the problem by placing dense physical markers on the body surface, which allows to extract realistic meshes from their non-rigid motions.
Ranked #1 on 3D Human Pose Estimation on Surreal
no code implementations • 7 Aug 2022 • Yifu Zhang, Chunyu Wang, Xinggang Wang, Wenjun Zeng, Wenyu Liu
To address the problem, we present an efficient approach to compute a marginal probability for each pair of objects in real time.
no code implementations • 31 Jul 2022 • Zihao Yin, Ping Gong, Chunyu Wang, Yizhou Yu, Yizhou Wang
As an important upstream task for many medical applications, supervised landmark localization still requires non-negligible annotation costs to achieve desirable performance.
1 code implementation • 22 Jul 2022 • Hang Ye, Wentao Zhu, Chunyu Wang, Rujie Wu, Yizhou Wang
While the voxel-based methods have achieved promising results for multi-person 3D pose estimation from multi-cameras, they suffer from heavy computation burdens, especially for large scenes.
Ranked #5 on 3D Multi-Person Pose Estimation on Campus
1 code implementation • 20 Jul 2022 • Jiajun Su, Chunyu Wang, Xiaoxuan Ma, Wenjun Zeng, Yizhou Wang
While monocular 3D pose estimation seems to have achieved very accurate results on the public datasets, their generalization ability is largely overlooked.
3D Multi-Person Pose Estimation (absolute) 3D Pose Estimation
1 code implementation • CVPR 2022 • Fei Xie, Chunyu Wang, Guangting Wang, Yue Cao, Wankou Yang, Wenjun Zeng
In contrast to the Siamese-like feature extraction, our network deeply embeds cross-image feature correlation in multiple layers of the feature network.
1 code implementation • 5 Dec 2021 • Fei Xie, Chunyu Wang, Guangting Wang, Wankou Yang, Wenjun Zeng
We present a Siamese-like Dual-branch network based on solely Transformers for tracking.
no code implementations • 30 Nov 2021 • Xiaotian Han, Quanzeng You, Chunyu Wang, Zhizheng Zhang, Peng Chu, Houdong Hu, Jiang Wang, Zicheng Liu
This dataset provides a more reliable benchmark of multi-camera, multi-object tracking systems in cluttered and crowded environments.
Ranked #2 on Object Tracking on MMPTRACK
1 code implementation • NeurIPS 2021 • Manjin Kim, Heeseung Kwon, Chunyu Wang, Suha Kwak, Minsu Cho
Convolution has been arguably the most important feature transform for modern neural networks, leading to the advance of deep learning.
Ranked #11 on Action Recognition on Diving-48
no code implementations • 5 Aug 2021 • Yifu Zhang, Chunyu Wang, Xinggang Wang, Wenyu Liu, Wenjun Zeng
We estimate 3D poses from the voxel representation by predicting whether each voxel contains a particular body joint.
Ranked #7 on 3D Multi-Person Pose Estimation on Panoptic (using extra training data)
1 code implementation • CVPR 2021 • Xiaoxuan Ma, Jiajun Su, Chunyu Wang, Hai Ci, Yizhou Wang
By comparing the two methods, we found that the end-to-end training scheme in GNN and the limb length constraints in PSM are two complementary factors to improve results.
Ranked #60 on 3D Human Pose Estimation on MPI-INF-3DHP (AUC metric)
no code implementations • 11 Dec 2020 • Ye Li, Kangning Yin, Jie Liang, Chunyu Wang, Guangqiang Yin
To solve these problems, we propose a Multi-task Joint Framework for real-time person search (MJF), which optimizes the person detection, feature extraction and identity comparison respectively.
1 code implementation • ICCV 2021 • Rongchang Xie, Chunyu Wang, Wenjun Zeng, Yizhou Wang
The state-of-the-art methods are consistency-based which learn about unlabeled images by encouraging the model to give consistent predictions for images under different augmentations.
2 code implementations • 26 Oct 2020 • Zhe Zhang, Chunyu Wang, Weichao Qiu, Wenhu Qin, Wenjun Zeng
To make the task truly unconstrained, we present AdaFuse, an adaptive multiview fusion method, which can enhance the features in occluded views by leveraging those in visible views.
Ranked #1 on 3D Human Pose Estimation on Total Capture
2 code implementations • ECCV 2020 • Hanyue Tu, Chunyu Wang, Wen-Jun Zeng
In contrast to the previous efforts which require to establish cross-view correspondence based on noisy and incomplete 2D pose estimations, we present an end-to-end solution which directly operates in the $3$D space, therefore avoids making incorrect decisions in the 2D space.
Ranked #5 on 3D Multi-Person Pose Estimation on Panoptic (using extra training data)
32 code implementations • 4 Apr 2020 • Yifu Zhang, Chunyu Wang, Xinggang Wang, Wen-Jun Zeng, Wenyu Liu
Formulating MOT as multi-task learning of object detection and re-ID in a single network is appealing since it allows joint optimization of the two tasks and enjoys high computation efficiency.
Ranked #1 on Multi-Object Tracking on 2DMOT15 (using extra training data)
no code implementations • CVPR 2020 • Rongchang Xie, Chunyu Wang, Yizhou Wang
Cross view feature fusion is the key to address the occlusion problem in human pose estimation.
1 code implementation • CVPR 2020 • Zhe Zhang, Chunyu Wang, Wenhu Qin, Wen-Jun Zeng
Then we lift the multi-view 2D poses to the 3D space by an Orientation Regularized Pictorial Structure Model (ORPSM) which jointly minimizes the projection error between the 3D and 2D poses, along with the discrepancy between the 3D pose and IMU orientations.
Ranked #1 on 3D Absolute Human Pose Estimation on Total Capture
1 code implementation • ICCV 2019 • Haibo Qiu, Chunyu Wang, Jingdong Wang, Naiyan Wang, Wen-Jun Zeng
It consists of two separate steps: (1) estimating the 2D poses in multi-view images and (2) recovering the 3D poses from the multi-view 2D poses.
Ranked #6 on 3D Human Pose Estimation on Total Capture
no code implementations • ECCV 2018 • Jieru Mei, Chunyu Wang, Wen-Jun Zeng
The archetypes generally correspond to the extremal points in the dataset and are learned by requiring them to be convex combinations of the training data.
no code implementations • ECCV 2018 • Hai Ci, Chunyu Wang, Yizhou Wang
We address the problem of video object segmentation which outputs the masks of a target object throughout a video given only a bounding box in the first frame.
no code implementations • 30 Jan 2018 • Peng Tang, Chunyu Wang, Xinggang Wang, Wenyu Liu, Wen-Jun Zeng, Jingdong Wang
In particular, our method improves results by 8. 8% over the static image detector for fast moving objects.
no code implementations • CVPR 2016 • Chunyu Wang, Yizhou Wang, Alan L. Yuille
Recognizing an action from a sequence of 3D skeletal poses is a challenging task.
no code implementations • 12 Dec 2014 • Chunyu Wang, John Flynn, Yizhou Wang, Alan L. Yuille
We show that under this restriction, building a model with simplices amounts to constructing a convex hull inside the sphere whose boundary facets is close to the data.
no code implementations • CVPR 2014 • Chunyu Wang, Yizhou Wang, Zhouchen Lin, Alan L. Yuille, Wen Gao
We address the challenges in three ways: (i) We represent a 3D pose as a linear combination of a sparse set of bases learned from 3D human skeletons.
Ranked #27 on 3D Human Pose Estimation on HumanEva-I
no code implementations • CVPR 2013 • Chunyu Wang, Yizhou Wang, Alan L. Yuille
We start by improving a state of the art method for estimating human joint locations from videos.