1 code implementation • CVPR 2020 • Sida Peng, Wen Jiang, Huaijin Pi, Xiuli Li, Hujun Bao, Xiaowei Zhou
Based on deep snake, we develop a two-stage pipeline for instance segmentation: initial contour proposal and contour deformation, which can handle errors in object localization.
Ranked #2 on Semantic Contour Prediction on Sbd val
no code implementations • 1 Jan 2021 • Hanqing Yang, Huaijin Pi, SABA GHORBANI BARZEGAR, Yu Zhang
This paper analyzes the serious false positive problem in OSOD and proposes a Focus on Classification One-Shot Object Detection (FOC OSOD) framework, which is improved in two important aspects: (1) classification cascade head with the fixed IoU threshold can enhance the robustness of classification by comparing multiple close regions; (2) classification region deformation on the query feature and the reference feature to obtain a more effective comparison region.
no code implementations • 15 Nov 2021 • Huaijin Pi, Huiyu Wang, Yingwei Li, Zizhang Li, Alan Yuille
In order to effectively search in this huge architecture space, we propose Hierarchical Sampling for better training of the supernet.
1 code implementation • 17 Jul 2022 • Zizhang Li, Mengmeng Wang, Huaijin Pi, Kechun Xu, Jianbiao Mei, Yong liu
However, the redundant parameters within the network structure can cause a large model size when scaling up for desirable performance.
Ranked #4 on Video Reconstruction on UVG
no code implementations • ICCV 2023 • Huaijin Pi, Sida Peng, Minghui Yang, Xiaowei Zhou, Hujun Bao
This paper presents a novel approach to generating the 3D motion of a human interacting with a target object, with a focus on solving the challenge of synthesizing long-range and diverse motions, which could not be fulfilled by existing auto-regressive models or path planning-based methods.