OneCanvas: 3D Scene Understanding via Panoramic Reprojection

arXiv:2606.19253 · cs.CV, cs.AI, cs.LG, cs.RO · Submitted 2026-06-17 · Read on arXiv

cs.CV, cs.AI, cs.LG, cs.RO

Submitted: 2026-06-17

Updated: 2026-09-27

Project page: https://baranowskibrt.github.io/onecanvas

Terminology

• Accuracy — 9× in this paper · explained in 1 episode
• Fine-Tuning — 7× in this paper · explained in 5 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Adaptation — 5× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Grounding — 5× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 4× in this paper
• Aggregation — 3× in this paper · explained in 1 episode
• Embodied AI — 3× in this paper · explained in 2 episodes
• Sparsity — 3× in this paper · explained in 4 episodes
• Core — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• International Conference on Computer Vision — 2× in this paper
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Two-stage training — 2× in this paper · explained in 2 episodes
• Visual Grounding — 2× in this paper · explained in 2 episodes
• 3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Frozen model — 1× in this paper · explained in 3 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• In International Conference on Learning Representations — 1× in this paper
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• Qwen3-VL Technical Report
• SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards
• Thinking with Spatial Code for Physical-World Video Reasoning
• 3D Aware Region Prompted Vision Language Model
• Video-R1: Reinforcing Video Reasoning in MLLMs
• Visuospatial Cognitive Assistant
• LiftProj: Space Lifting and Projection-Based Panorama Stitching
• PanoGrounder: Bridging 2D and 3D with Panoramic Scene Representations for VLM-based 3D Visual Grounding
• PanoEnv: Exploring 3D Spatial Intelligence in Panoramic Environments with Reinforcement Learning
• When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
• Do 3D Large Language Models Really Understand 3D Spatial Relationships?
• SpaceR: Reinforcing MLLMs in Video Spatial Reasoning
• Loc3R-VLM: Language-based Localization and 3D Reasoning with Vision-Language Models
• Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes
• Visual Spatial Tuning
• SpaceMind: Camera-Guided Modality Fusion for Spatial Reasoning in Vision-Language Models
• PANORAMA: The Rise of Omnidirectional Vision in the Embodied AI Era

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