23 citations · 61 across the 15 of their papers we have counts for
7 papers · 1 filter
Efficient Segment Anything with Depth-Aware Fusion and Limited Training Data
Yiming Zhou, Xuenjie Xie, Panfeng Li +3
Segment Anything Models (SAM) achieve impressive universal segmentation performance but require massive datasets (e.g., 11M images) and rely solely on RGB inputs. Recent efficient…
Classifier-Centric Adaptive Framework for Open-Vocabulary Camouflaged Object Segmentation
Hanyu Zhang, Yiming Zhou, Jinxia Zhang
Open-vocabulary camouflaged object segmentation requires models to segment camouflaged objects of arbitrary categories unseen during training, placing extremely high demands on gen…
Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods
Yiming Zhou, Zixuan Zeng, Andi Chen +7
Exploring the capabilities of Neural Radiance Fields (NeRF) and Gaussian-based methods in the context of 3D scene reconstruction, this study contrasts these modern approaches with…
Mapping New Realities: Ground Truth Image Creation with Pix2Pix Image-to-Image Translation
Zhenglin Li, Bo Guan, Yuanzhou Wei +3
Generative Adversarial Networks (GANs) have significantly advanced image processing, with Pix2Pix being a notable framework for image-to-image translation. This paper explores a no…
A Multi-Source Data Fusion-based Semantic Segmentation Model for Relic Landslide Detection
Yiming Zhou, Yuexing Peng, Daqing Ge +2
As a natural disaster, landslide often brings tremendous losses to human lives, so it urgently demands reliable detection of landslide risks. When detecting relic landslides that p…
SimpleNet: A Simple Network for Image Anomaly Detection and Localization
Zhikang Liu, Yiming Zhou, Yuansheng Xu +1
We propose a simple and application-friendly network (called SimpleNet) for detecting and localizing anomalies. SimpleNet consists of four components: (1) a pre-trained Feature Ext…
Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search
Xin Li, Yiming Zhou, Zheng Pan +1
Achieving good speed and accuracy trade-off on a target platform is very important in deploying deep neural networks in real world scenarios. However, most existing automatic archi…