1 code implementation • 15 Sep 2023 • Zhihao Hu, Yiran Xu, Mengnan Du, Jindong Gu, Xinmei Tian, Fengxiang He
Our adaptive reweighing method prioritizes samples closer to the decision boundary and assigns a higher weight to improve the generalizability of fair classifiers.
1 code implementation • 15 Aug 2023 • XiMing Xing, Chuang Wang, Haitao Zhou, Zhihao Hu, Chongxuan Li, Dong Xu, Qian Yu
In the full-control inversion process, we propose an appearance-energy function to control the color and texture of the final generated photo. Importantly, our Inversion-by-Inversion pipeline is training-free and can accept different types of exemplars for color and texture control.
no code implementations • 26 Jul 2023 • Zhihao Hu, Dong Xu
In this work, by using the diffusion model with ControlNet, we proposed a new motion-guided video-to-video translation framework called VideoControlNet to generate various videos based on the given prompts and the condition from the input video.
no code implementations • CVPR 2023 • Zhihao Hu, Dong Xu
In this work, we propose the complexity-guided slimmable decoder (cgSlimDecoder) in combination with skip-adaptive entropy coding (SaEC) for efficient deep video compression.
no code implementations • 20 Dec 2022 • Guanbo Pan, Guo Lu, Zhihao Hu, Dong Xu
Although several content adaptive methods have been proposed by updating the encoder-side components, the adaptability of both latents and the decoder is not well exploited.
no code implementations • CVPR 2022 • Zhihao Hu, Guo Lu, Jinyang Guo, Shan Liu, Wei Jiang, Dong Xu
The previous deep video compression approaches only use the single scale motion compensation strategy and rarely adopt the mode prediction technique from the traditional standards like H. 264/H. 265 for both motion and residual compression.
no code implementations • CVPR 2022 • Zhenghao Chen, Guo Lu, Zhihao Hu, Shan Liu, Wei Jiang, Dong Xu
In this work, we propose the first end-to-end optimized framework for compressing automotive stereo videos (i. e., stereo videos from autonomous driving applications) from both left and right views.
no code implementations • CVPR 2021 • Zhihao Hu, Guo Lu, Dong Xu
In this work, we propose a feature-space video coding network (FVC) by performing all major operations (i. e., motion estimation, motion compression, motion compensation and residual compression) in the feature space.
1 code implementation • ICCV 2021 • Xiaolei Wu, Zhihao Hu, Lu Sheng, Dong Xu
In this work, we propose a new feed-forward arbitrary style transfer method, referred to as StyleFormer, which can simultaneously fulfill fine-grained style diversity and semantic content coherency.
no code implementations • 22 Sep 2020 • Weitao Feng, Zhihao Hu, Baopu Li, Weihao Gan, Wei Wu, Wanli Ouyang
Besides, we propose a new MOT evaluation measure, Still Another IDF score (SAIDF), aiming to focus more on identity issues. This new measure may overcome some problems of the previous measures and provide a better insight for identity issues in MOT.
no code implementations • ECCV 2020 • Zhihao Hu, Zhenghao Chen, Dong Xu, Guo Lu, Wanli Ouyang, Shuhang Gu
In this work, we propose a new framework called Resolution-adaptive Flow Coding (RaFC) to effectively compress the flow maps globally and locally, in which we use multi-resolution representations instead of single-resolution representations for both the input flow maps and the output motion features of the MV encoder.
1 code implementation • 9 Feb 2020 • Jiaheng Liu, Guo Lu, Zhihao Hu, Dong Xu
Our EDIC method can also be readily incorporated with the Deep Video Compression (DVC) framework to further improve the video compression performance.
no code implementations • 18 Jan 2019 • Weitao Feng, Zhihao Hu, Wei Wu, Junjie Yan, Wanli Ouyang
In this paper, we propose a unified Multi-Object Tracking (MOT) framework learning to make full use of long term and short term cues for handling complex cases in MOT scenes.