Papers Transparent objects
“Transparent objects” 태그가 달린 논문 117편 · 필터 해제
Depth Restoration of Hand-Held Transparent Objects for Human-to-Robot Handover
Transparent objects are common in daily life, while their optical properties pose challenges for RGB-D cameras to capture accurate depth information. This issue is further amplified when these objects are hand-held, as h…
Depth EstimationTransparent objectsDistillGrasp: Integrating Features Correlation with Knowledge Distillation for Depth Completion of Transparent Objects
Due to the visual properties of reflection and refraction, RGB-D cameras cannot accurately capture the depth of transparent objects, leading to incomplete depth maps. To fill in the missing points, recent studies tend to…
Depth CompletionFeature CorrelationKnowledge DistillationRobotic Grasping+1DepGAN: Leveraging Depth Maps for Handling Occlusions and Transparency in Image Composition
Image composition is a complex task which requires a lot of information about the scene for an accurate and realistic composition, such as perspective, lighting, shadows, occlusions, and object interactions. Previous met…
Generative Adversarial NetworkOcclusion HandlingTransparent objectsNeST: Neural Stress Tensor Tomography by leveraging 3D Photoelasticity
Photoelasticity enables full-field stress analysis in transparent objects through stress-induced birefringence. Existing techniques are limited to 2D slices and require destructively slicing the object. Recovering the in…
ObjectTransparent objectsTransparent Object Depth Completion
The perception of transparent objects for grasp and manipulation remains a major challenge, because existing robotic grasp methods which heavily rely on depth maps are not suitable for transparent objects due to their un…
Depth CompletionDepth EstimationObjectTransparent objectsInfluence of Water Droplet Contamination for Transparency Segmentation
Computer vision techniques are on the rise for industrial applications, like process supervision and autonomous agents, e.g., in the healthcare domain and dangerous environments. While the general usability of these tech…
Transparent objectsResidual-NeRF: Learning Residual NeRFs for Transparent Object Manipulation
Transparent objects are ubiquitous in industry, pharmaceuticals, and households. Grasping and manipulating these objects is a significant challenge for robots. Existing methods have difficulty reconstructing complete dep…
NeRFObjectTransparent objectsSpider: A Unified Framework for Context-dependent Concept Segmentation
Different from the context-independent (CI) concepts such as human, car, and airplane, context-dependent (CD) concepts require higher visual understanding ability, such as camouflaged object and medical lesion. Despite t…
Transparent objectsSAID-NeRF: Segmentation-AIDed NeRF for Depth Completion of Transparent Objects
Acquiring accurate depth information of transparent objects using off-the-shelf RGB-D cameras is a well-known challenge in Computer Vision and Robotics. Depth estimation/completion methods are typically employed and trai…
Depth CompletionDepth EstimationNeRFNovel View Synthesis+2Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting
In this work, we propose a novel method to supervise 3D Gaussian Splatting (3DGS) scenes using optical tactile sensors. Optical tactile sensors have become widespread in their use in robotics for manipulation and object …
3DGSDepth EstimationMonocular Depth EstimationTransparent objectsSELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation
Autonomous self-improving robots that interact and improve with experience are key to the real-world deployment of robotic systems. In this paper, we propose an online learning method, SELFI, that leverages online robot …
Collision Avoidancereinforcement-learningReinforcement LearningSocial Navigation+1A New Dataset and a Distractor-Aware Architecture for Transparent Object Tracking
Performance of modern trackers degrades substantially on transparent objects compared to opaque objects. This is largely due to two distinct reasons. Transparent objects are unique in that their appearance is directly af…
2kObjectObject TrackingTransparent objectsDifferentiable Neural Surface Refinement for Modeling Transparent Objects
Neural implicit surface reconstruction leveraging volume rendering has led to significant advances in multi-view reconstruction. However results for transparent objects can be very poor primarily because the renderin…
Novel View SynthesisSurface ReconstructionTransparent objectsEfficientPPS: Part-aware Panoptic Segmentation of Transparent Objects for Robotic Manipulation
The use of autonomous robots for assistance tasks in hospitals has the potential to free up qualified staff and im-prove patient care. However, the ubiquity of deformable and transparent objects in hospital settings pose…
Panoptic SegmentationPart-aware Panoptic SegmentationTransparent objectsNeural Radiance Fields for Transparent Object Using Visual Hull
Unlike opaque object, novel view synthesis of transparent object is a challenging task, because transparent object refracts light of background causing visual distortions on the transparent object surface along the viewp…
NeRFNovel View SynthesisObjectTransparent objectsGaussian Splatting SLAM
We present the first application of 3D Gaussian Splatting in monocular SLAM, the most fundamental but the hardest setup for Visual SLAM. Our method, which runs live at 3fps, utilises Gaussians as the only 3D representati…
3DGS3D ReconstructionNovel View SynthesisTransparent objectsCascade-Zero123: One Image to Highly Consistent 3D with Self-Prompted Nearby Views
Synthesizing multi-view 3D from one single image is a significant but challenging task. Zero-1-to-3 methods have achieved great success by lifting a 2D latent diffusion model to the 3D scope. The target view image is gen…
Transparent objectsStableDreamer: Taming Noisy Score Distillation Sampling for Text-to-3D
In the realm of text-to-3D generation, utilizing 2D diffusion models through score distillation sampling (SDS) frequently leads to issues such as blurred appearances and multi-faced geometry, primarily due to the intrins…
3D GenerationText to 3DTransparent objectsRFTrans: Leveraging Refractive Flow of Transparent Objects for Surface Normal Estimation and Manipulation
Transparent objects are widely used in our daily lives, making it important to teach robots to interact with them. However, it's not easy because the reflective and refractive effects can make depth cameras fail to give …
global-optimizationSurface Normal EstimationTransparent objectsTabletop Transparent Scene Reconstruction via Epipolar-Guided Optical Flow with Monocular Depth Completion Prior
Reconstructing transparent objects using affordable RGB-D cameras is a persistent challenge in robotic perception due to inconsistent appearances across views in the RGB domain and inaccurate depth readings in each singl…
3D ReconstructionDepth CompletionOptical Flow EstimationSemantic Segmentation+1