1.1k citations · 1.1k across the 11 of their papers we have counts for
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YOLO-UniOW: Efficient Universal Open-World Object Detection
Lihao Liu, Juexiao Feng, Hui Chen +4
Traditional object detection models are constrained by the limitations of closed-set datasets, detecting only categories encountered during training. While multimodal models have e…
Promptable Anomaly Segmentation with SAM Through Self-Perception Tuning
Hui-Yue Yang, Hui Chen, Ao Wang +7
Segment Anything Model (SAM) has made great progress in anomaly segmentation tasks due to its impressive generalization ability. However, existing methods that directly apply SAM t…
[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs
Ao Wang, Fengyuan Sun, Hui Chen +3
Multimodal Large Language Models (MLLMs) have recently demonstrated strong performance across a wide range of vision-language tasks, garnering significant attention in the computer…
PrefixKV: Adaptive Prefix KV Cache is What Vision Instruction-Following Models Need for Efficient Generation
Ao Wang, Hui Chen, Jiaxin Li +6
Recently, large vision-language models (LVLMs) have rapidly gained popularity for their strong generation and reasoning capabilities given diverse multimodal inputs. However, these…
YOLOv10: Real-Time End-to-End Object Detection
Ao Wang, Hui Chen, Lihao Liu +4
Over the past years, YOLOs have emerged as the predominant paradigm in the field of real-time object detection owing to their effective balance between computational cost and detec…