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Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity
Recent advances in text-guided image compression have shown great potential to enhance the perceptual quality of reconstructed images.
Neural Video Compression with Temporal Layer-Adaptive Hierarchical B-frame Coding
We first extend an existing unidirectional NVC model to a bidirectional model, which achieves -21. 13% BD-rate gain over the unidirectional baseline model.
SeeThroughNet: Resurrection of Auxiliary Loss by Preserving Class Probability Information
In order to calculate the auxiliary loss between the feature maps of intermediate layers and the ground truth in the field of semantic segmentation, the size of each feature map must match the ground truth.
Unsupervised Representation Transfer for Small Networks: I Believe I Can Distill On-the-Fly
In this work, we propose a novel unsupervised learning framework for small networks that combines deep self-supervised representation learning and knowledge distillation within one-phase training.
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