SCORP: Scene-Consistent Object Refinement via Proxy Generation and Tuning
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Abstract (arXiv)
Viewpoint missing of objects is common in scene reconstruction, as camera paths typically prioritize capturing the overall scene structure rather than individual objects. This makes it highly challenging to achieve high-fidelity object-level modeling while maintaining accurate scene-level representation. Addressing this issue is critical for advancing downstream tasks requiring high-fidelity object reconstruction. In this paper, we introduce Scene-Consistent Object Refinement via Proxy Generation and Tuning (SCORP), a novel 3D enhancement framework that leverages 3D generative priors to recover fine-grained object geometry and appearance under missing views. Starting with proxy generation by substituting degraded objects using a 3D generation model, SCORP then progressively refines geometry and texture by aligning each proxy to its degraded counterpart in 7-DoF pose, followed by correcting spatial and appearance inconsistencies through registration-constrained enhancement. This two-stage proxy tuning ensures the high-fidelity geometry and appearance of the original object in unseen views while maintaining consistency in spatial positioning, observed geometry, and appearance. Across challenging benchmarks, SCORP achieves consistent gains over recent state-of-the-art baselines on both novel view synthesis and geometry completion tasks. SCORP is available at https://github.com/PolySummit/SCORP.
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References · 55
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2025Qwen2.5-VL Technical Reportcited by 5,587
- 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
- 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
- 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,332
- 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,117
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
- 2024SAM 2: Segment Anything in Images and Videoscited by 2,863
- 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
- 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
38 more
- 2021MUSIQ: Multi-scale Image Quality Transformercited by 1,081
- 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,076
- 2024Grounding Image Matching in 3D with MASt3Rcited by 983
- 2019The Replica Dataset: A Digital Replica of Indoor Spacescited by 904
- 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
- 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 770
- 2018Open3D: A Modern Library for 3D Data Processingcited by 721
- 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
- 2022Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemscited by 612
- 2023LERF: Language Embedded Radiance Fieldscited by 543
- 2019BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networkscited by 490
- 2021Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesiscited by 464
- 2022PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategiescited by 436
- 2018PCN: Point Completion Networkcited by 384
- 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 326
- 2021PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformerscited by 286
- 2017Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metricscited by 264
- 2024DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalizationcited by 256
- 2021Learning Object-Compositional Neural Radiance Field for Editable Scene Renderingcited by 228
- 2022AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domainscited by 208
- 2020GRNet: Gridding Residual Network for Dense Point Cloud Completioncited by 174
- 2021SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformercited by 164
- 2025Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Modelscited by 161
- 2023DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Modelscited by 127
- 20243DGS-Enhancer: Enhancing Unbounded 3D Gaussian Splatting with View-consistent 2D Diffusion Priorscited by 106
- 2022Vision Transformer for NeRF-Based View Synthesis from a Single Input Imagecited by 104
- 2023Learning to Render Novel Views from Wide-Baseline Stereo Pairscited by 104
- 2022SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformercited by 83
- 2023Nerfbusters: Removing Ghostly Artifacts from Casually Captured NeRFscited by 76
- 2023AdaPoinTr: Diverse Point Cloud Completion with Adaptive Geometry-Aware Transformerscited by 67
- 2016A Large Dataset of Object Scanscited by 64
- 2025GenFusion: Closing the Loop between Reconstruction and Generation via Videoscited by 41
- 2024GenNBV: Generalizable Next-Best-View Policy for Active 3D Reconstructioncited by 39
- 2023Point-Cloud Completion with Pretrained Text-to-image Diffusion Modelscited by 37
- 2025Decompositional Neural Scene Reconstruction with Generative Diffusion Priorcited by 31
- 2022LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypointscited by 27
- 2023Perceptual Quality Assessment of NeRF and Neural View Synthesis Methods for Front-Facing Viewscited by 17
- 20243DGS-CD: 3D Gaussian Splatting-based Change Detection for Physical Object Rearrangementcited by 15
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