Papers Transparent objects
“Transparent objects” 태그가 달린 논문 117편 · 필터 해제
Trans2k: Unlocking the Power of Deep Models for Transparent Object Tracking
Visual object tracking has focused predominantly on opaque objects, while transparent object tracking received very little attention. Motivated by the uniqueness of transparent objects in that their appearance is directl…
2kObjectObject TrackingTransparent objects+1TODE-Trans: Transparent Object Depth Estimation with Transformer
Transparent objects are widely used in industrial automation and daily life. However, robust visual recognition and perception of transparent objects have always been a major challenge. Currently, most commercial-grade d…
Depth EstimationObjectTransparent Object Depth EstimationTransparent objectsPolarimetric Inverse Rendering for Transparent Shapes Reconstruction
In this work, we propose a novel method for the detailed reconstruction of transparent objects by exploiting polarimetric cues. Most of the existing methods usually lack sufficient constraints and suffer from the over-sm…
Inverse RenderingTransparent objectsTransNet: Category-Level Transparent Object Pose Estimation
Transparent objects present multiple distinct challenges to visual perception systems. First, their lack of distinguishing visual features makes transparent objects harder to detect and localize than opaque objects. Even…
Depth CompletionObjectPose EstimationSurface Normal Estimation+1Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects
Commercial depth sensors usually generate noisy and missing depths, especially on specular and transparent objects, which poses critical issues to downstream depth or point cloud-based tasks. To mitigate this problem, we…
Pose EstimationTransparent objectsTransMatting: Enhancing Transparent Objects Matting with Transformers
Image matting refers to predicting the alpha values of unknown foreground areas from natural images. Prior methods have focused on propagating alpha values from known to unknown regions. However, not all natural images h…
DecoderImage MattingTransparent objectsPhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects
Object pose estimation is crucial for robotic applications and augmented reality. Beyond instance level 6D object pose estimation methods, estimating category-level pose and shape has become a promising trend. As such, a…
6D Pose Estimation using RGBObjectPose EstimationTransparent objectsExploring the Interactive Guidance for Unified and Effective Image Matting
Recent image matting studies are developing towards proposing trimap-free or interactive methods for complete complex image matting tasks. Although avoiding the extensive labors of trimap annotation, existing methods sti…
Foreground SegmentationImage MattingTransparent objectsHybrid Mesh-neural Representation for 3D Transparent Object Reconstruction
We propose a novel method to reconstruct the 3D shapes of transparent objects using hand-held captured images under natural light conditions. It combines the advantage of explicit mesh and multi-layer perceptron (MLP) ne…
Image MattingObject ReconstructionTransparent objectsRGB-Depth Fusion GAN for Indoor Depth Completion
The raw depth image captured by the indoor depth sensor usually has an extensive range of missing depth values due to inherent limitations such as the inability to perceive transparent objects and limited distance range.…
Depth CompletionTransparent objectsClearPose: Large-scale Transparent Object Dataset and Benchmark
Transparent objects are ubiquitous in household settings and pose distinct challenges for visual sensing and perception systems. The optical properties of transparent objects leave conventional 3D sensors alone unreliabl…
BenchmarkingDepth CompletionObjectPose Estimation+1TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baseline
Transparent objects are common in our daily life and frequently handled in the automated production line. Robust vision-based robotic grasping and manipulation for these objects would be beneficial for automation. Howeve…
Depth CompletionRobotic GraspingTransparent Object Depth EstimationTransparent objectsPolarimetric Pose Prediction
Light has many properties that vision sensors can passively measure. Colour-band separated wavelength and intensity are arguably the most commonly used for monocular 6D object pose estimation. This paper explores how com…
6D Pose Estimation using RGBObjectPose EstimationPose Prediction+2Dex-NeRF: Using a Neural Radiance Field to Grasp Transparent Objects
The ability to grasp and manipulate transparent objects is a major challenge for robots. Existing depth cameras have difficulty detecting, localizing, and inferring the geometry of such objects. We propose using neural r…
NeRFTransparent objectsSeeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects
The basis of many object manipulation algorithms is RGB-D input. Yet, commodity RGB-D sensors can only provide distorted depth maps for a wide range of transparent objects due light refraction and absorption. To tackle t…
Depth CompletionTransparent objectsStereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation
We present a large-scale stereo RGB image object pose estimation dataset named the $\textbf{StereOBJ-1M}$ dataset. The dataset is designed to address challenging cases such as object transparency, translucency, and specu…
6D Pose Estimation using RGBObjectPose EstimationTransparent objectsTrans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance
Transparent objects, such as glass walls and doors, constitute architectural obstacles hindering the mobility of people with low vision or blindness. For instance, the open space behind glass doors is inaccessible, unles…
DecoderGPUNavigateScene Segmentation+2SuperCaustics: Real-time, open-source simulation of transparent objects for deep learning applications
Transparent objects are a very challenging problem in computer vision. They are hard to segment or classify due to their lack of precise boundaries, and there is limited data available for training deep neural networks. …
Caustics SegmentationDepth CompletionObject DetectionPhysical Simulations+5Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World
Common fully glazed facades and transparent objects present architectural barriers and impede the mobility of people with low vision or blindness, for instance, a path detected behind a glass door is inaccessible unless …
DecoderNavigateSemantic SegmentationTransparent objectsSimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo
Robot manipulation of unknown objects in unstructured environments is a challenging problem due to the variety of shapes, materials, arrangements and lighting conditions. Even with large-scale real-world data collection,…
Keypoint DetectionObjectobject-detectionObject Detection+3