Papers 3D Shape Reconstruction
“3D Shape Reconstruction” 태그가 달린 논문 150편 · 필터 해제
SEMAGIC: Learning Semantically Consistent Deformable 3D Representations from In-the-Wild Images
Learning deformable 3D object models from single-view in-the-wild images has enabled impressive 3D shape reconstruction without supervision. However, it remains unclear whether these models capture the semantic structure…
3D Shape ReconstructionSemantic correspondenceShapeGrasp: Simultaneous Visuo-Haptic Shape Completion and Grasping for Improved Robot Manipulation
Humans grasp unfamiliar objects by combining an initial visual estimate with tactile and proprioceptive feedback during interaction. We present ShapeGrasp, a robotic implementation of this approach. The proposed method i…
3D Shape ReconstructionRobot ManipulationHighly Deformable Proprioceptive Membrane for Real-Time 3D Shape Reconstruction
Reconstructing the three-dimensional (3D) geometry of object surfaces is essential for robot perception, yet vision-based approaches degrade under low illumination or occlusion. This limitation motivates the design of a …
3D Shape ReconstructionActive Cross-Modal Visuo-Tactile Perception of Deformable Linear Objects
This paper presents a novel cross-modal visuo-tactile perception framework for the 3D shape reconstruction of deformable linear objects (DLOs), with a specific focus on cables subject to severe visual occlusions. Unlike …
3D Shape ReconstructionInstance SegmentationPoint CloudsVoroLight: Learning Voronoi Surface Meshes via Sphere Intersection
Voronoi diagrams naturally produce convex, watertight, and topologically consistent cells, making them an appealing representation for 3D shape reconstruction. However, standard differentiable Voronoi approaches typicall…
3D Shape ReconstructionPoint CloudsRadar2Shape: 3D Shape Reconstruction from High-Frequency Radar using Multiresolution Signed Distance Functions
Determining the shape of 3D objects from high-frequency radar signals is analytically complex but critical for commercial and aerospace applications. Previous deep learning methods have been applied to radar modeling; ho…
3D Shape Reconstruction3D ReconstructionWave-Former: Through-Occlusion 3D Reconstruction via Wireless Shape Completion
We present Wave-Former, a novel method capable of high-accuracy 3D shape reconstruction for completely occluded, diverse, everyday objects. This capability can open new applications spanning robotics, augmented reality, …
3D Shape Reconstruction3D ReconstructionEstimating Continuum Robot Shape under External Loading using Spatiotemporal Neural Networks
This paper presents a learning-based approach for accurately estimating the 3D shape of flexible continuum robots subjected to external loads. The proposed method introduces a spatiotemporal neural network architecture t…
3D Shape ReconstructionPoint CloudsThermal Polarimetric Multi-view Stereo
This paper introduces a novel method for detailed 3D shape reconstruction utilizing thermal polarization cues. Unlike state-of-the-art methods, the proposed approach is independent of illumination and material properties…
3D Shape ReconstructionMeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds
Reconstructing 3D objects into editable programs is pivotal for applications like reverse engineering and shape editing. However, existing methods often rely on limited domain-specific languages (DSLs) and small-scale da…
3D Shape ReconstructionCode GenerationPoint CloudsFLAIR: Frequency- and Locality-Aware Implicit Neural Representations
Implicit Neural Representations (INRs) leverage neural networks to map coordinates to corresponding signals, enabling continuous and compact representations. This paradigm has driven significant advances in various visio…
3D Shape ReconstructionNovel View SynthesisBandRC: Band Shifted Raised Cosine Activated Implicit Neural Representations
In recent years, implicit neural representations(INRs) have gained popularity in the computer vision community. This is mainly due to the strong performance of INRs in many computer vision tasks. These networks can extra…
3D Shape ReconstructionDenoisingImage ReconstructionSuper-ResolutionSparSplat: Fast Multi-View Reconstruction with Generalizable 2D Gaussian Splatting
Recovering 3D information from scenes via multi-view stereo reconstruction (MVS) and novel view synthesis (NVS) is inherently challenging, particularly in scenarios involving sparse-view setups. The advent of 3D Gaussian…
3DGS3D Reconstruction3D Scene Reconstruction3D Shape Reconstruction+13D Object Reconstruction with mmWave Radars
This paper presents RFconstruct, a framework that enables 3D shape reconstruction using commercial off-the-shelf (COTS) mmWave radars for self-driving scenarios. RFconstruct overcomes radar limitations of low angular res…
3D Object Reconstruction3D Shape ReconstructionDecoderObject+13D Shape Completion using Multi-Resolution Spectral Encoding
Reconstruction of intricate local patterns and large missing regions during 3D shape completion has the contradictory requirements of computation over a wider context and operations for finer detail restoration. To this …
3D Inpainting3D Shape Generation3D Shape ReconstructionHyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
To efficiently adapt large models or to train generative models of neural representations, Hypernetworks have drawn interest. While hypernetworks work well, training them is cumbersome, and often requires ground truth op…
3D Shape ReconstructionImage GenerationPersonalized Image GenerationProbeSDF: Light Field Probes for Neural Surface Reconstruction
SDF-based differential rendering frameworks have achieved state-of-the-art multiview 3D shape reconstruction. In this work, we re-examine this family of approaches by minimally reformulating its core appearance model in …
3D Shape ReconstructionSurface ReconstructionFrom Transparent to Opaque: Rethinking Neural Implicit Surfaces with $α$-NeuS
Traditional 3D shape reconstruction techniques from multi-view images, such as structure from motion and multi-view stereo, face challenges in reconstructing transparent objects. Recent advances in neural radiance fields…
3D Shape ReconstructionTransparent objectsGuide3D: A Bi-planar X-ray Dataset for 3D Shape Reconstruction
Endovascular surgical tool reconstruction represents an important factor in advancing endovascular tool navigation, which is an important step in endovascular surgery. However, the lack of publicly available datasets sig…
3D Reconstruction3D Shape ReconstructionActiveNeuS: Neural Signed Distance Fields for Active Stereo
3D-shape reconstruction in extreme environments, such as low illumination or scattering condition, has been an open problem and intensively researched. Active stereo is one of potential solution for such environments for…
3D Shape Reconstruction