Zobrazeno 1 - 10
of 400
pro vyhledávání: '"Cao, Si"'
Autor:
Yu, Zhu, Pang, Bowen, Liu, Lizhe, Zhang, Runmin, Peng, Qihao, Luo, Maochun, Yang, Sheng, Chen, Mingxia, Cao, Si-Yuan, Shen, Hui-Liang
We introduce LOcc, an effective and generalizable framework for open-vocabulary occupancy (OVO) prediction. Previous approaches typically supervise the networks through coarse voxel-to-text correspondences via image features as intermediates or noisy
Externí odkaz:
http://arxiv.org/abs/2411.16072
Autor:
Ying, Jiacheng, Liu, Mushui, Wu, Zhe, Zhang, Runming, Yu, Zhu, Fu, Siming, Cao, Si-Yuan, Wu, Chao, Yu, Yunlong, Shen, Hui-Liang
Blind face restoration has made great progress in producing high-quality and lifelike images. Yet it remains challenging to preserve the ID information especially when the degradation is heavy. Current reference-guided face restoration approaches eit
Externí odkaz:
http://arxiv.org/abs/2411.14125
Autor:
Yu, Junchen, Cao, Si-Yuan, Zhang, Runmin, Zhang, Chenghao, Hu, Jianxin, Yu, Zhu, Yu, Beinan, Shen, Hui-liang
We propose a novel unsupervised cross-modal homography estimation framework, based on interleaved modality transfer and self-supervised homography prediction, named InterNet. InterNet integrates modality transfer and self-supervised homography estima
Externí odkaz:
http://arxiv.org/abs/2409.17993
This article introduces BEVPlace++, a novel, fast, and robust LiDAR global localization method for unmanned ground vehicles. It uses lightweight convolutional neural networks (CNNs) on Bird's Eye View (BEV) image-like representations of LiDAR data to
Externí odkaz:
http://arxiv.org/abs/2408.01841
Autor:
Zhang, Runmin, Ma, Jun, Cao, Si-Yuan, Luo, Lun, Yu, Beinan, Chen, Shu-Jie, Li, Junwei, Shen, Hui-Liang
We propose a novel unsupervised cross-modal homography estimation framework based on intra-modal Self-supervised learning, Correlation, and consistent feature map Projection, namely SCPNet. The concept of intra-modal self-supervised learning is first
Externí odkaz:
http://arxiv.org/abs/2407.08148
Autor:
Zhang, Xue, Cao, Si-Yuan, Wang, Fang, Zhang, Runmin, Wu, Zhe, Zhang, Xiaohan, Bai, Xiaokai, Shen, Hui-Liang
Most recent multispectral object detectors employ a two-branch structure to extract features from RGB and thermal images. While the two-branch structure achieves better performance than a single-branch structure, it overlooks inference efficiency. Th
Externí odkaz:
http://arxiv.org/abs/2405.16038
Autor:
Yu, Zhu, Zhang, Runmin, Ying, Jiacheng, Yu, Junchen, Hu, Xiaohai, Luo, Lun, Cao, Si-Yuan, Shen, Hui-Liang
Vision-based Semantic Scene Completion (SSC) has gained much attention due to its widespread applications in various 3D perception tasks. Existing sparse-to-dense approaches typically employ shared context-independent queries across various input ima
Externí odkaz:
http://arxiv.org/abs/2405.13675
SGDFormer: One-stage Transformer-based Architecture for Cross-Spectral Stereo Image Guided Denoising
Autor:
Zhang, Runmin, Yu, Zhu, Sheng, Zehua, Ying, Jiacheng, Cao, Si-Yuan, Chen, Shu-Jie, Yang, Bailin, Li, Junwei, Shen, Hui-Liang
Cross-spectral image guided denoising has shown its great potential in recovering clean images with rich details, such as using the near-infrared image to guide the denoising process of the visible one. To obtain such image pairs, a feasible and econ
Externí odkaz:
http://arxiv.org/abs/2404.00349
Autor:
Zheng, Shuhang, Li, Yixuan, Yu, Zhu, Yu, Beinan, Cao, Si-Yuan, Wang, Minhang, Xu, Jintao, Ai, Rui, Gu, Weihao, Luo, Lun, Shen, Hui-Liang
Place recognition is an important technique for autonomous cars to achieve full autonomy since it can provide an initial guess to online localization algorithms. Although current methods based on images or point clouds have achieved satisfactory perf
Externí odkaz:
http://arxiv.org/abs/2303.01043
Autor:
Cao, Si1 (AUTHOR), Su, Han1 (AUTHOR), Zhang, Xiaoyi2 (AUTHOR), Fang, Chao3 (AUTHOR), Wu, Nayiyuan3 (AUTHOR), Zeng, Youjie1 (AUTHOR) zengyoujie1995@gmail.com, Chen, Minghua1 (AUTHOR) 7633013@qq.com
Publikováno v:
Brain & Behavior. Oct2024, Vol. 14 Issue 10, p1-8. 8p.
