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Found 8 papers, 3 papers with code
SAI3D: Segment Any Instance in 3D Scenes
Advancements in 3D instance segmentation have traditionally been tethered to the availability of annotated datasets, limiting their application to a narrow spectrum of object categories.
Towards Robust Probabilistic Modeling on SO(3) via Rotation Laplace Distribution
With this benefit, we demonstrate its advantages in semi-supervised rotation regression, where the pseudo labels are noisy.
Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling
Normalizing flows (NFs) provide a powerful tool to construct an expressive distribution by a sequence of trackable transformations of a base distribution and form a probabilistic model of underlying data.
A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation
Rotation Laplace distribution is robust to the disturbance of outliers and enforces much gradient to the low-error region, resulting in a better convergence.
FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filtering
Inspired by the popular semi-supervised approach, FixMatch, we propose to leverage pseudo label filtering to facilitate the information flow from labeled data to unlabeled data in a teacher-student mutual learning framework.
Projective Manifold Gradient Layer for Deep Rotation Regression
Regressing rotations on SO(3) manifold using deep neural networks is an important yet unsolved problem.
Towards Accurate Active Camera Localization
These approaches localize the camera in the discrete pose space and are agnostic to the localization-driven scene property, which restricts the camera pose accuracy in the coarse scale.
Single image reflection removal via learning with multi-image constraints
Reflections are very common phenomena in our daily photography, which distract people's attention from the scene behind the glass.
