no code implementations • 9 Jan 2024 • Xiaojuan Wang, Taesung Park, Yang Zhou, Eli Shechtman, Richard Zhang
We leverage the appearance of the subject from the other source frames in the video, fusing it with a mid-level representation driven by DensePose keypoints and face landmarks.
no code implementations • 4 Dec 2023 • Xiaojuan Wang, Janne Kontkanen, Brian Curless, Steve Seitz, Ira Kemelmacher, Ben Mildenhall, Pratul Srinivasan, Dor Verbin, Aleksander Holynski
We present a method that uses a text-to-image model to generate consistent content across multiple image scales, enabling extreme semantic zooms into a scene, e. g., ranging from a wide-angle landscape view of a forest to a macro shot of an insect sitting on one of the tree branches.
3 code implementations • 15 Dec 2022 • Yabo Xiao, Kai Su, Xiaojuan Wang, Dongdong Yu, Lei Jin, Mingshu He, Zehuan Yuan
The existing end-to-end methods rely on dense representations to preserve the spatial detail and structure for precise keypoint localization.
1 code implementation • 8 Oct 2022 • Yabo Xiao, Xiaojuan Wang, Dongdong Yu, Kai Su, Lei Jin, Mei Song, Shuicheng Yan, Jian Zhao
With the proposed body representation, we further deliver a compact single-stage multi-person pose regression network, termed as AdaptivePose.
no code implementations • 4 Jan 2022 • Yabo Xiao, Dongdong Yu, Xiaojuan Wang, Lei Jin, Guoli Wang, Qian Zhang
Off-the-shelf single-stage multi-person pose regression methods generally leverage the instance score (i. e., confidence of the instance localization) to indicate the pose quality for selecting the pose candidates.
no code implementations • CVPR 2022 • Lei Jin, Chenyang Xu, Xiaojuan Wang, Yabo Xiao, Yandong Guo, Xuecheng Nie, Jian Zhao
The existing multi-person absolute 3D pose estimation methods are mainly based on two-stage paradigm, i. e., top-down or bottom-up, leading to redundant pipelines with high computation cost.
1 code implementation • 27 Dec 2021 • Yabo Xiao, Xiaojuan Wang, Dongdong Yu, Guoli Wang, Qian Zhang, Mingshu He
Multi-person pose estimation methods generally follow top-down and bottom-up paradigms, both of which can be considered as two-stage approaches thus leading to the high computation cost and low efficiency.
no code implementations • 23 Aug 2021 • Jian Zhao, Gang Wang, Jianan Li, Lei Jin, Nana Fan, Min Wang, Xiaojuan Wang, Ting Yong, Yafeng Deng, Yandong Guo, Shiming Ge, Guodong Guo
The 2nd Anti-UAV Workshop \& Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking.
no code implementations • 13 Apr 2020 • Yabo Xiao, Dongdong Yu, Xiaojuan Wang, Tianqi Lv, Yiqi Fan, Lingrui Wu
To alleviate these issues, we propose a novel Spatial Preserve and Content-aware Network(SPCNet), which includes two effective modules: Dilated Hourglass Module(DHM) and Selective Information Module(SIM).
no code implementations • CVPR 2016 • Xiaojuan Wang, Ting Zhang, Guo-Jun Q, Jinhui Tang, Jingdong Wang
In this paper, we address the problem of searching for semantically similar images from a large database.
no code implementations • ICCV 2015 • Xiang Li, Wei-Shi Zheng, Xiaojuan Wang, Tao Xiang, Shaogang Gong
In real world person re-identification (re-id), images of people captured at very different resolutions from different locations need be matched.