no code implementations • 22 Dec 2023 • Dongmei Zhang, Chang Li, Ray Zhang, Shenghao Xie, Wei Xue, Xiaodong Xie, Shanghang Zhang
In this work, we propose FM-OV3D, a method of Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D Detection, which improves the open-vocabulary localization and recognition abilities of 3D model by blending knowledge from multiple pre-trained foundation models, achieving true open-vocabulary without facing constraints from original 3D datasets.
no code implementations • 19 Oct 2023 • Yichuan Deng, Zhao Song, Shenghao Xie, Chiwun Yang
In the realm of deep learning, transformers have emerged as a dominant architecture, particularly in natural language processing tasks.
1 code implementation • 22 Aug 2023 • Yizhen Yuan, Rui Kong, Shenghao Xie, Yuanchun Li, Yunxin Liu
However, most backdoor attacks have to modify the neural network models through training with poisoned data and/or direct model editing, which leads to a common but false belief that backdoor attack can be easily avoided by properly protecting the model.
no code implementations • 16 Aug 2023 • Yichuan Deng, Zhao Song, Shenghao Xie
Softmax unit and ReLU unit are the key structure in attention computation.
no code implementations • 5 Jul 2023 • Yeqi Gao, Zhao Song, Shenghao Xie
Given matrices $A_1 \in \mathbb{R}^{n \times d}$, and $A_2 \in \mathbb{R}^{n \times d}$ and $B \in \mathbb{R}^{n \times n}$, the purpose is to solve some certain optimization problems: Normalized version $\min_{X} \| D(X)^{-1} \exp(A_1 X A_2^\top) - B \|_F^2$ and Rescaled version $\| \exp(A_1 X A_2^\top) - D(X) \cdot B \|_F^2$.
no code implementations • 24 Mar 2023 • Yulin Luo, Rui Zhao, Xiaobao Wei, Jinwei Chen, Yijie Lu, Shenghao Xie, Tianyu Wang, Ruiqin Xiong, Ming Lu, Shanghang Zhang
To this end, we propose a method called Weather-aware Multi-scale MoE (WM-MoE) based on Transformer for blind weather removal.