UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
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Updated
Dec 23, 2025 - Python
UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
This work proposes a feature refined end-to-end object tracking framework with a balanced performance using a high-level feature refine tracking framework. The feature refine module enhances the target feature representation power that allows the network to capture salient information to locate the target.
HierbaNetV1 is a novel convolutional neural network (CNN) architecture with a cutting-edge feature extraction technique
ML classifier trained with raw pixels as features and high level features and then comparing their accuracies
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