EPISODE · Dec 24, 2025 · 26 MIN
The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding
from Daily Paper Cast · host Jingwen Liang, Gengyu Wang
🤗 Upvotes: 53 | cs.CV Authors: Weichen Fan, Haiwen Diao, Quan Wang, Dahua Lin, Ziwei Liu Title: The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding Arxiv: http://arxiv.org/abs/2512.19693v1 Abstract: Deep representations across modalities are inherently intertwined. In this paper, we systematically analyze the spectral characteristics of various semantic and pixel encoders. Interestingly, our study uncovers a highly inspiring and rarely explored correspondence between an encoder's feature spectrum and its functional role: semantic encoders primarily capture low-frequency components that encode abstract meaning, whereas pixel encoders additionally retain high-frequency information that conveys fine-grained detail. This heuristic finding offers a unifying perspective that ties encoder behavior to its underlying spectral structure. We define it as the Prism Hypothesis, where each data modality can be viewed as a projection of the natural world onto a shared feature spectrum, just like the prism. Building on this insight, we propose Unified Autoencoding (UAE), a model that harmonizes semantic structure and pixel details via an innovative frequency-band modulator, enabling their seamless coexistence. Extensive experiments on ImageNet and MS-COCO benchmarks validate that our UAE effectively unifies semantic abstraction and pixel-level fidelity into a single latent space with state-of-the-art performance.
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🤗 Upvotes: 53 | cs.CV Authors: Weichen Fan, Haiwen Diao, Quan Wang, Dahua Lin, Ziwei Liu Title: The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding Arxiv: http://arxiv.org/abs/2512.19693v1 Abstract: Deep representations across modalities are inherently intertwined. In this paper, we systematically analyze the spectral characteristics of various semantic and pixel encoders. Interestingly, our study uncovers a highly inspiring and rarely explored correspondence between an encoder's feature spectrum and its functional role: semantic encoders primarily capture low-frequency components that encode abstract meaning, whereas pixel encoders additionally retain high-frequency information that conveys fine-grained detail. This heuristic finding offers a unifying perspective that ties encoder behavior to its underlying spectral structure. We define it as the Prism Hypothesis, where each data modality can be viewed as a projection of the natural world onto a shared feature spectrum, just like the prism. Building on this insight, we propose Unified Autoencoding (UAE), a model that harmonizes semantic structure and pixel details via an innovative frequency-band modulator, enabling their seamless coexistence. Extensive experiments on ImageNet and MS-COCO benchmarks validate that our UAE effectively unifies semantic abstraction and pixel-level fidelity into a single latent space with state-of-the-art performance.
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The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding
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