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ZMNet: feature fusion and semantic boundary supervision for real-time semantic segmentation
Feature fusion module is an essential component of real-time semantic segmentation networks to bridge the semantic gap among different feature...
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Semantic segmentation-assisted instance feature fusion for multi-level 3D part instance segmentation
Recognizing 3D part instances from a 3D point cloud is crucial for 3D structure and scene understanding. Several learning-based approaches use...
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ASGSA: global semantic-aware network for action segmentation
Action segmentation is vital for video understanding because it heuristically divides complex untrimmed videos into short semantic clips. Real-world...
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Position attention optimized deep semantic segmentation
Semantic segmentation can be applied in various fields of computer vision such as scene understanding. In order to assist intelligent machines to...
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Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow
In this paper, we focus on exploring effective methods for faster and accurate semantic segmentation. A common practice to improve the performance is...
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Benchmarking the Robustness of LiDAR Semantic Segmentation Models
When using LiDAR semantic segmentation models for safety-critical applications such as autonomous driving, it is essential to understand and improve...
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Segmentation from localization: a weakly supervised semantic segmentation method for resegmenting CAM
Semantic segmentation has wide applications in computer vision tasks. Due to the high labor cost of pixel-level annotation, weakly supervised...
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Identification of optimal semantic segmentation architecture for the segmentation of hepatic structures from computed tomography images
Automatic segmentation of various hepatic structures from computed tomography images is of great importance in surgery and treatment planning for...
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HybridNet: Integrating Multiple Approaches for Aerial Semantic Segmentation
In recent times, semantic segmentation for VHR aerial images has become an emerging research topic due to its widespread applications in disaster...
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Class-conditional domain adaptation for semantic segmentation
Semantic segmentation is an important sub-task for many applications. However, pixel-level ground-truth labeling is costly, and there is a tendency...
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Robust semantic segmentation method of urban scenes in snowy environment
Semantic segmentation plays a crucial role in various computer vision tasks, such as autonomous driving in urban scenes. The related researches have...
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Interaction semantic segmentation network via progressive supervised learning
Semantic segmentation requires both low-level details and high-level semantics, without losing too much detail and ensuring the speed of inference....
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Visual representations with texts domain generalization for semantic segmentation
At present, Domain generalization for semantic segmentation relying on deep neural networks has made little progress. Most of the current methods are...
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Rainy day image semantic segmentation based on two-stage progressive network
Semantic segmentation plays a crucial role in the fields of computer vision and computer graphics, with extensive applications in various practical...
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PPNet : pooling position attention network for semantic segmentation
Semantic segmentation with attention module has made great progress in many computer vision tasks. However, attention modules ignore some boundary...
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ContourNet: Research on Contour Based Nighttime Semantic Segmentation
Due to the scarcity of nighttime semantic segmentation datasets and the high demand for network models, the development of semantic segmentation of...
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Few-shot semantic segmentation in complex industrial components
In the semantic segmentation of complex industrial parts, it is usually impossible to obtain enough defective industrial parts for training. This...
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Learnable scene prior for point cloud semantic segmentation
In this paper, we propose a Geo-SceneEncoder framework to handle point cloud scene semantic segmentation, including a SceneEncoder to learn a scene...
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SSNet: a joint learning network for semantic segmentation and disparity estimation
Joint learning for semantic segmentation and disparity estimation is adopted to scene parsing for mutual benefit. However, existing joint learning...
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Scaling Up Multi-domain Semantic Segmentation with Sentence Embeddings
The state-of-the-art semantic segmentation methods have achieved impressive performance on predefined close-set individual datasets, but their...
