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Found 26 papers, 16 papers with code
RPMArt: Towards Robust Perception and Manipulation for Articulated Objects
Our primary contribution is a Robust Articulation Network (RoArtNet) that is able to predict both joint parameters and affordable points robustly by local feature learning and point tuple voting.
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis
The DSE module, designed for real-world autonomous driving scenarios, enhances the semantic perception of point clouds, particularly for distant points.
GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects
Results show that GAMMA significantly outperforms SOTA articulation modeling and manipulation algorithms in unseen and cross-category articulated objects.
Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation
In this work, we propose the first framework for restoring videos from all adverse weather conditions by developing a video adverse-weather-component suppression network (ViWS-Net).
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in point cloud completion: understanding faithful global shapes from incomplete point clouds and generating high-accuracy local structures.
CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame
CRIN directly takes the coordinates of points as input and transforms local points into rotation-invariant representations via centrifugal reference frames.
One-Shot General Object Localization
In contrast, our proposed OneLoc algorithm efficiently finds the object center and bounding box size by a special voting scheme.
CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregation
We introduce a novel method, CPPF++, designed for sim-to-real pose estimation.
PSFormer: Point Transformer for 3D Salient Object Detection
We propose PSFormer, an effective point transformer model for 3D salient object detection.
LBF:Learnable Bilateral Filter For Point Cloud Denoising
Bilateral filter (BF) is a fast, lightweight and effective tool for image denoising and well extended to point cloud denoising.
SPCNet: Stepwise Point Cloud Completion Network
We propose a novel stepwise point cloud completion network (SPCNet) for various 3D models with large missings.
SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation
The SO(3)-equivariant features communicate with RGB features to deduce the (missed) geometry for detecting keypoints of an object with the reflective surface from the depth channel.
CF-YOLO: Cross Fusion YOLO for Object Detection in Adverse Weather with a High-quality Real Snow Dataset
To our knowledge, RSOD is the first quantitatively evaluated and graded snowy OD dataset.
CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
Drawing inspirations from traditional point pair features (PPFs), in this paper, we design a novel Category-level PPF (CPPF) voting method to achieve accurate, robust and generalizable 9D pose estimation in the wild.
Ranked #8 on
6D Pose Estimation using RGBD
on REAL275
Understanding Pixel-level 2D Image Semantics with 3D Keypoint Knowledge Engine
Pixel-level 2D object semantic understanding is an important topic in computer vision and could help machine deeply understand objects (e. g. functionality and affordance) in our daily life.
PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features
Spherical Voxel Convolution and Point Re-sampling are proposed to extract rotation invariant features for each point.
Deep Texture-Aware Features for Camouflaged Object Detection
Camouflaged object detection is a challenging task that aims to identify objects having similar texture to the surroundings.
Memory-Efficient Modeling and Slicing of Large-Scale Adaptive Lattice Structures
The presented methods have been validated by a series of case studies with large number (up to 100M) of struts to demonstrate its applicability to large-scale lattice structures.
Computational Geometry
UKPGAN: A General Self-Supervised Keypoint Detector
Keypoint detection is an essential component for the object registration and alignment.
Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes
In the work, we disentangle the direct offset into Local Canonical Coordinates (LCC), box scales and box orientations.
Semantic Correspondence via 2D-3D-2D Cycle
Visual semantic correspondence is an important topic in computer vision and could help machine understand objects in our daily life.
KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations
Detecting 3D objects keypoints is of great interest to the areas of both graphics and computer vision.
Human Correspondence Consensus for 3D Object Semantic Understanding
Semantic understanding of 3D objects is crucial in many applications such as object manipulation.
Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Clutter
This paper focuses on robotic picking tasks in cluttered scenario.
Combinational Q-Learning for Dou Di Zhu
Deep reinforcement learning (DRL) has gained a lot of attention in recent years, and has been proven to be able to play Atari games and Go at or above human levels.
Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown.
