Zobrazeno 1 - 10
of 157
pro vyhledávání: '"Le, Xinyi"'
Significant focus has been placed on integrating large language models (LLMs) with various tools in developing general-purpose agents. This poses a challenge to LLMs' tool-use capabilities. However, there are evident gaps between existing tool-use ev
Externí odkaz:
http://arxiv.org/abs/2407.08713
Anomaly detection with only prior knowledge from normal samples attracts more attention because of the lack of anomaly samples. Existing CNN-based pixel reconstruction approaches suffer from two concerns. First, the reconstruction source and target a
Externí odkaz:
http://arxiv.org/abs/2209.01816
Despite the rapid advance of unsupervised anomaly detection, existing methods require to train separate models for different objects. In this work, we present UniAD that accomplishes anomaly detection for multiple classes with a unified framework. Un
Externí odkaz:
http://arxiv.org/abs/2206.03687
The local reference frame (LRF), as an independent coordinate system generated on a local 3D surface, is widely used in 3D local feature descriptor construction and 3D transformation estimation which are two key steps in the local method-based surfac
Externí odkaz:
http://arxiv.org/abs/2204.08024
Autor:
Wang, Yuchao, Wang, Haochen, Shen, Yujun, Fei, Jingjing, Li, Wei, Jin, Guoqiang, Wu, Liwei, Zhao, Rui, Le, Xinyi
The crux of semi-supervised semantic segmentation is to assign adequate pseudo-labels to the pixels of unlabeled images. A common practice is to select the highly confident predictions as the pseudo ground-truth, but it leads to a problem that most p
Externí odkaz:
http://arxiv.org/abs/2203.03884
This work studies the problem of few-shot object counting, which counts the number of exemplar objects (i.e., described by one or several support images) occurring in the query image. The major challenge lies in that the target objects can be densely
Externí odkaz:
http://arxiv.org/abs/2201.08959
In this paper, we propose a Point Fractal Network (PF-Net), a novel learning-based approach for precise and high-fidelity point cloud completion. Unlike existing point cloud completion networks, which generate the overall shape of the point cloud fro
Externí odkaz:
http://arxiv.org/abs/2003.00410
Autor:
Chen, Binhao, Gong, Liang, Yu, Chenrui, Du, Xiaofeng, Chen, Jianhuan, Xie, Shenghan, Le, Xinyi, Li, Yanming, Liu, Chengliang
Publikováno v:
In Computers and Electronics in Agriculture December 2023 215
Publikováno v:
In Journal of the Franklin Institute November 2023 360(17):14075-14097
3D local feature extraction and matching is the basis for solving many tasks in the area of computer vision, such as 3D registration, modeling, recognition and retrieval. However, this process commonly draws into false correspondences, due to noise,
Externí odkaz:
http://arxiv.org/abs/1901.05104