Unverified50% confidenceFactExact time
Disentanglement can eliminate the view bias of learned expression encodings, enabling the encoding to serve as a driving signal for multi-view consistent avatars.
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Long-term
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10/19/2026
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UnverifiedThe paper points out that learned expression encodings suffer from severe view bias, i.e., the encoding results unintentionally absorb information about camera viewpoint, lighting, and head orientation.72% similarUnverifiedMulti-reference image input can decouple different visual dimensions, giving the model more independent constraint signals when processing character identity and scene environment, and reducing mutual interference between visual elements.72% similarUnverifiedIncreasing the resolution of visual input is one of the practical paths to alleviating the limitations of VLM visual encoders.71% similarUnverifiedThe visual capabilities of multimodal models are typically implemented through a visual encoder, with common approaches including pre-trained visual models such as ViT or SigLIP.69% similar
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