1 code implementation • 4 Mar 2024 • Huali Xu, Li Liu, Shuaifeng Zhi, Shaojing Fu, Zhuo Su, Ming-Ming Cheng, Yongxiang Liu
For this reason, this paper explores a Source-Free CDFSL (SF-CDFSL) problem, in which CDFSL is addressed through the use of existing pretrained models instead of training a model with source data, avoiding accessing source data.
1 code implementation • ICCV 2023 • Jingjia Shi, Shuaifeng Zhi, Kai Xu
3D plane recovery from a single image can usually be divided into several subtasks of plane detection, segmentation, parameter estimation and possibly depth estimation.
1 code implementation • 17 Jul 2023 • Liu Liu, Shuaifeng Zhi, Zhenhua Du, Li Liu, Xinyu Zhang, Kai Huo, Weidong Jiang
In this paper, we propose a hybrid point-wise Radar-Optical fusion approach for object detection in autonomous driving scenarios.
no code implementations • 11 Jul 2023 • Shuzhou Sun, Shuaifeng Zhi, Qing Liao, Janne Heikkilä, Li Liu
To remedy this, we propose Two-stage Causal Modeling (TsCM) for the SGG task, which takes the long-tailed distribution and semantic confusion as confounders to the Structural Causal Model (SCM) and then decouples the causal intervention into two stages.
no code implementations • 15 Mar 2023 • Huali Xu, Shuaifeng Zhi, Shuzhou Sun, Vishal M. Patel, Li Liu
Deep learning has been highly successful in computer vision with large amounts of labeled data, but struggles with limited labeled training data.
no code implementations • 7 Feb 2023 • Junwen Huang, Alexey Artemov, Yujin Chen, Shuaifeng Zhi, Kai Xu, Matthias Nießner
In this work, we explore a central 3D scene modeling task, namely, semantic scene reconstruction without using any 3D annotations.
no code implementations • 17 Aug 2022 • Huali Xu, Shuaifeng Zhi, Li Liu
The goal of Cross-Domain Few-Shot Classification (CDFSC) is to accurately classify a target dataset with limited labelled data by exploiting the knowledge of a richly labelled auxiliary dataset, despite the differences between the domains of the two datasets.
no code implementations • 29 Nov 2021 • Shuaifeng Zhi, Edgar Sucar, Andre Mouton, Iain Haughton, Tristan Laidlow, Andrew J. Davison
ILabel's underlying model is a multilayer perceptron (MLP) trained from scratch in real-time to learn a joint neural scene representation.
2 code implementations • ICLR 2022 • Shikun Liu, Shuaifeng Zhi, Edward Johns, Andrew J. Davison
We present ReCo, a contrastive learning framework designed at a regional level to assist learning in semantic segmentation.
no code implementations • ICCV 2021 • Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger, Andrew J. Davison
Semantic labelling is highly correlated with geometry and radiance reconstruction, as scene entities with similar shape and appearance are more likely to come from similar classes.
no code implementations • CVPR 2019 • Shuaifeng Zhi, Michael Bloesch, Stefan Leutenegger, Andrew J. Davison
Systems which incrementally create 3D semantic maps from image sequences must store and update representations of both geometry and semantic entities.