1 citations · 1 across the 2 of their papers we have counts for
7 papers
SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection
Qiangang Du, Jinlong Peng, Xu Chen +4
In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets based on paired data. However,…
SDDF: Specificity-Driven Dynamic Focusing for Open-Vocabulary Camouflaged Object Detection
Jiaming Liang, Yifeng Zhan, Chunlin Liu +6
Open-vocabulary object detection (OVOD) aims to detect known and unknown objects in the open world by leveraging text prompts. Benefiting from the emergence of large-scale vision--…
PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models
Qingdong He, Jinlong Peng, Zhengkai Jiang +2
Recent success of vision foundation models have shown promising performance for the 2D perception tasks. However, it is difficult to train a 3D foundation network directly due to t…
P3P: Pseudo-3D Pre-training for Scaling 3D Voxel-based Masked Autoencoders
Xuechao Chen, Ying Chen, Jialin Li +5
3D pre-training is crucial to 3D perception tasks. Nevertheless, limited by the difficulties in collecting clean and complete 3D data, 3D pre-training has persistently faced data s…
Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes
Donghao Zhou, Jialin Li, Jinpeng Li +7
Large-scale well-annotated datasets are of great importance for training an effective object detector. However, obtaining accurate bounding box annotations is laborious and demandi…
Decision Boundary-aware Knowledge Consolidation Generates Better Instance-Incremental Learner
Qiang Nie, Weifu Fu, Yuhuan Lin +5
Instance-incremental learning (IIL) focuses on learning continually with data of the same classes. Compared to class-incremental learning (CIL), the IIL is seldom explored because…