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20212023
most citedThe Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition

13 citations · 14 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

Self-Supervised Class-Agnostic Motion Prediction with Spatial and Temporal Consistency Regularizations

Kewei Wang, Yizheng Wu, Jun Cen +5

The perception of motion behavior in a dynamic environment holds significant importance for autonomous driving systems, wherein class-agnostic motion prediction methods directly pr…

cs.CV20241 cited

Using Left and Right Brains Together: Towards Vision and Language Planning

Jun Cen, Chenfei Wu, Xiao Liu +6

Large Language Models (LLMs) and Large Multi-modality Models (LMMs) have demonstrated remarkable decision masking capabilities on a variety of tasks. However, they inherently opera…

cs.CV2023

Enlarging Instance-specific and Class-specific Information for Open-set Action Recognition

Jun Cen, Shiwei Zhang, Xiang Wang +4

Open-set action recognition is to reject unknown human action cases which are out of the distribution of the training set. Existing methods mainly focus on learning better uncertai…

cs.CV202313 cited

The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition

Jun Cen, Di Luan, Shiwei Zhang +5

Open-set Recognition (OSR) aims to identify test samples whose classes are not seen during the training process. Recently, Unified Open-set Recognition (UOSR) has been proposed to…

cs.CV20221 cited

Open-world Semantic Segmentation for LIDAR Point Clouds

Jun Cen, Peng Yun, Shiwei Zhang +5

Current methods for LIDAR semantic segmentation are not robust enough for real-world applications, e.g., autonomous driving, since it is closed-set and static. The closed-set assum…

cs.CV2021

Open-set 3D Object Detection

Jun Cen, Peng Yun, Junhao Cai +2

3D object detection has been wildly studied in recent years, especially for robot perception systems. However, existing 3D object detection is under a closed-set condition, meaning…