CamPVG is the first diffusion-based framework for generating geometrically consistent panoramic videos from camera pose inputs using a panoramic Plücker embedding and spherical epipolar attention module.
Imagine360: Immersive 360 video generation from perspective anchor
6 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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A generative model produces realistic and coherent 360 panoramic videos from in-the-wild perspective videos via curated online data and geometry-motion aware operations.
PermaVid disentangles spatial context into semantic appearance and geometric structure via multi-modal memory banks and edit-aware updates to maintain long-term consistency in video generation after edits.
Rein3D generates photorealistic, globally consistent 3D indoor scenes by using a restore-and-refine process where radial panoramic videos are restored via diffusion models and then used to update a 3D Gaussian field.
PanoSAM2 adapts SAM2 with a Pano-Aware Decoder, Distortion-Guided Mask Loss, and Long-Short Memory Module to improve 360 video object segmentation, reporting +5.6 and +6.7 gains over base SAM2 on two benchmarks.
Pantheon360 introduces a controllable 360° video diffusion framework that uses an explicit 3D cache from sparse inputs to enforce geometric consistency for digital twin generation.
citing papers explorer
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CamPVG: Camera-Controlled Panoramic Video Generation with Epipolar-Aware Diffusion
CamPVG is the first diffusion-based framework for generating geometrically consistent panoramic videos from camera pose inputs using a panoramic Plücker embedding and spherical epipolar attention module.
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Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos
A generative model produces realistic and coherent 360 panoramic videos from in-the-wild perspective videos via curated online data and geometry-motion aware operations.
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PermaVid: Consistent Video Generation Across Edits via Disentangled Context Memory
PermaVid disentangles spatial context into semantic appearance and geometric structure via multi-modal memory banks and edit-aware updates to maintain long-term consistency in video generation after edits.
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Rein3D: Reinforced 3D Indoor Scene Generation with Panoramic Video Diffusion Models
Rein3D generates photorealistic, globally consistent 3D indoor scenes by using a restore-and-refine process where radial panoramic videos are restored via diffusion models and then used to update a 3D Gaussian field.
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PanoSAM2: Lightweight Distortion- and Memory-aware Adaptions of SAM2 for 360 Video Object Segmentation
PanoSAM2 adapts SAM2 with a Pano-Aware Decoder, Distortion-Guided Mask Loss, and Long-Short Memory Module to improve 360 video object segmentation, reporting +5.6 and +6.7 gains over base SAM2 on two benchmarks.
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Pantheon360: Taming Digital Twin Generation via 3D-Aware 360{\deg} Video Diffusion
Pantheon360 introduces a controllable 360° video diffusion framework that uses an explicit 3D cache from sparse inputs to enforce geometric consistency for digital twin generation.