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Found 6 papers, 3 papers with code
Adaptive Mixed-Scale Feature Fusion Network for Blind AI-Generated Image Quality Assessment
Specifically, inspired by the characteristics of the human visual system and motivated by the observation that "visual quality" and "authenticity" are characterized by both local and global aspects, AMFF-Net scales the image up and down and takes the scaled images and original-sized image as the inputs to obtain multi-scale features.
Isotropic Gaussian Splatting for Real-Time Radiance Field Rendering
The 3D Gaussian splatting method has drawn a lot of attention, thanks to its high performance in training and high quality of the rendered image.
GCFAgg: Global and Cross-view Feature Aggregation for Multi-view Clustering
However, most existing deep clustering methods learn consensus representation or view-specific representations from multiple views via view-wise aggregation way, where they ignore structure relationship of all samples.
Reduced-Reference Quality Assessment of Point Clouds via Content-Oriented Saliency Projection
Many dense 3D point clouds have been exploited to represent visual objects instead of traditional images or videos.
PSNet: Parallel Symmetric Network for Video Salient Object Detection
Finally, we use the Importance Perception Fusion (IPF) module to fuse the features from two parallel branches according to their different importance in different scenarios.
Consensus Graph Learning for Multi-view Clustering
Furthermore, we unify the spectral embedding and low rank tensor learning into a unified optimization framework to determine the spectral embedding matrices and tensor representation jointly.
