most citedDeep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook

213 citations · 226 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning

Wenjun Miao, Guansong Pang, Trong-Tung Nguyen +3

Class incremental learning (CIL) aims to learn a model that can not only incrementally accommodate new classes, but also maintain the learned knowledge of old classes. Out-of-distr…

cs.CV20241 cited

Learning Transferable Negative Prompts for Out-of-Distribution Detection

Tianqi Li, Guansong Pang, Xiao Bai +2

Existing prompt learning methods have shown certain capabilities in Out-of-Distribution (OOD) detection, but the lack of OOD images in the target dataset in their training can lead…

cs.CV20243 cited

DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization

Jiahe Li, Jiawei Zhang, Xiao Bai +4

Radiance fields have demonstrated impressive performance in synthesizing novel views from sparse input views, yet prevailing methods suffer from high training costs and slow infere…

cs.CV2024

Robust Synthetic-to-Real Transfer for Stereo Matching

Jiawei Zhang, Jiahe Li, Lei Huang +4

With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains. However, few studies have in…

cs.CV2023213 cited

Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook

Huang Zhang, Changshuo Wang, Shengwei Tian +4

In recent years, point cloud representation has become one of the research hotspots in the field of computer vision, and has been widely used in many fields, such as autonomous dri…

cs.CV20234 cited

Unsupervised Recognition of Unknown Objects for Open-World Object Detection

Ruohuan Fang, Guansong Pang, Lei Zhou +2

Open-World Object Detection (OWOD) extends object detection problem to a realistic and dynamic scenario, where a detection model is required to be capable of detecting both known a…