A multimodal pipeline decodes EEG into 3D meshes via EEG-to-image, MLLM reasoning, diffusion, and single-image-to-3D conversion, reporting 85.4% 10-way accuracy and 0.648 CLIPScore.
Vist3a: Text-to-3d by stitching a multi-view reconstruction network to a video generator
3 Pith papers cite this work. Polarity classification is still indexing.
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UniRecGen unifies reconstruction and generation via shared canonical space and disentangled cooperative learning to produce complete, consistent 3D models from sparse views.
Splatent recovers fine details for latent-space 3D Gaussian Splatting by applying multi-view attention in 2D rather than reconstructing in 3D space.
citing papers explorer
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Brain3D: EEG-to-3D Decoding of Visual Representations via Multimodal Reasoning
A multimodal pipeline decodes EEG into 3D meshes via EEG-to-image, MLLM reasoning, diffusion, and single-image-to-3D conversion, reporting 85.4% 10-way accuracy and 0.648 CLIPScore.
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UniRecGen: Unifying Multi-View 3D Reconstruction and Generation
UniRecGen unifies reconstruction and generation via shared canonical space and disentangled cooperative learning to produce complete, consistent 3D models from sparse views.
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Splatent: Splatting Diffusion Latents for Novel View Synthesis
Splatent recovers fine details for latent-space 3D Gaussian Splatting by applying multi-view attention in 2D rather than reconstructing in 3D space.