no code implementations • 10 Sep 2023 • Shuangkang Fang, Yufeng Wang, Yi Yang, Yi-Hsuan Tsai, Wenrui Ding, Shuchang Zhou, Ming-Hsuan Yang
To tackle these issues, we introduce a text-driven editing method, termed DN2N, which allows for the direct acquisition of a NeRF model with universal editing capabilities, eliminating the requirement for retraining.
1 code implementation • 8 Apr 2023 • Shuangkang Fang, Yufeng Wang, Yi Yang, Weixin Xu, Heng Wang, Wenrui Ding, Shuchang Zhou
To address this limitation and maximize the potential of each architecture, we propose Progressive Volume Distillation with Active Learning (PVD-AL), a systematic distillation method that enables any-to-any conversions between different architectures.
1 code implementation • 3 Sep 2022 • Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu
Second, to improve the robustness of binary models with contextual dependencies, we compute the contextual dynamic embeddings to determine the binarization thresholds in general binary convolutional blocks.
no code implementations • 8 Dec 2021 • Xianlin Zeng, Yalong Jiang, Wenrui Ding, Hongguang Li, Yafeng Hao, Zifeng Qiu
High-level graph representations encode the trajectories of people and the interactions among multiple identities while low-level graph representations encode the local body postures of each person.
no code implementations • 14 Oct 2021 • Yufeng Wang, Yi-Hsuan Tsai, Wei-Chih Hung, Wenrui Ding, Shuo Liu, Ming-Hsuan Yang
Multi-Task Learning (MTL) aims to enhance the model generalization by sharing representations between related tasks for better performance.
1 code implementation • ECCV 2020 • Xiyang Liu, Jie Yang, Wenrui Ding
The crowd counting task aims at estimating the number of people located in an image or a frame from videos.
no code implementations • 25 Nov 2019 • Chunlei Liu, Wenrui Ding, Yuan Hu, Baochang Zhang, Jianzhuang Liu, Guodong Guo
The BGA method is proposed to modify the binary process of GBCNs to alleviate the local minima problem, which can significantly improve the performance of 1-bit DCNNs.
no code implementations • CVPR 2019 • Chunlei Liu, Wenrui Ding, Xin Xia, Baochang Zhang, Jiaxin Gu, Jianzhuang Liu, Rongrong Ji, David Doermann
The CiFs can be easily incorporated into existing deep convolutional neural networks (DCNNs), which leads to new Circulant Binary Convolutional Networks (CBCNs).
no code implementations • 24 Oct 2019 • Chunlei Liu, Wenrui Ding, Jinyu Yang, Vittorio Murino, Baochang Zhang, Jungong Han, Guodong Guo
In this paper, we propose a novel aggregation signature suitable for small object tracking, especially aiming for the challenge of sudden and large drift.
no code implementations • 21 Aug 2019 • Chunlei Liu, Wenrui Ding, Xin Xia, Yuan Hu, Baochang Zhang, Jianzhuang Liu, Bohan Zhuang, Guodong Guo
Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (DCNNs) for mobile and AI chips based applications.