Deep learning-based depth estimation methods from monocular image and videos: A comprehensive survey
Estimating depth from single RGB images and videos is of widespread interest due to its
applications in many areas, including autonomous driving, 3D reconstruction, digital …
applications in many areas, including autonomous driving, 3D reconstruction, digital …
HouseCat6D-A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision. Building on
successful instance-level approaches research is shifting towards category-level pose …
successful instance-level approaches research is shifting towards category-level pose …
Monograspnet: 6-dof grasping with a single rgb image
6-DoF robotic grasping is a long-lasting but un-solved problem. Recent methods utilize
strong 3D networks to extract geometric grasping representations from depth sensors …
strong 3D networks to extract geometric grasping representations from depth sensors …
Polarimetric 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 …
separated wavelength and intensity are arguably the most commonly used for monocular 6D …
Rapid network adaptation: Learning to adapt neural networks using test-time feedback
We propose a method for adapting neural networks to distribution shifts at test-time. In
contrast to training-time robustness mechanisms that attempt to anticipate the shift, we …
contrast to training-time robustness mechanisms that attempt to anticipate the shift, we …
On the importance of accurate geometry data for dense 3D vision tasks
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor
data. The respectively used principle of measuring distances provides advantages and …
data. The respectively used principle of measuring distances provides advantages and …
Learning accurate 3d shape based on stereo polarimetric imaging
Abstract Shape from Polarization (SfP) aims to recover surface normal using the polarization
cues of light. The accuracy of existing SfP methods is affected by two main problems. First …
cues of light. The accuracy of existing SfP methods is affected by two main problems. First …
SP: Self-Supervised Polarimetric Pose Prediction
This paper proposes the first self-supervised 6D object pose prediction from multimodal
RGB+ polarimetric images. The novel training paradigm comprises (1) a physical model to …
RGB+ polarimetric images. The novel training paradigm comprises (1) a physical model to …
Unsupervised spike depth estimation via cross-modality cross-domain knowledge transfer
Neuromorphic spike data, an upcoming modality with high temporal resolution, has shown
promising potential in autonomous driving by mitigating the challenges posed by high …
promising potential in autonomous driving by mitigating the challenges posed by high …
Wild tofu: Improving range and quality of indirect time-of-flight depth with rgb fusion in challenging environments
Indirect Time-of-Flight (I-ToF) imaging is a widespread way of depth estimation for mobile
devices due to its small size and affordable price. Previous works have mainly focused on …
devices due to its small size and affordable price. Previous works have mainly focused on …