Search Results for author:
Found 16 papers, 7 papers with code
S4Net: Single Stage Salient-Instance Segmentation
Taking into account the category-independent property of each target, we design a single stage salient instance segmentation framework, with a novel segmentation branch.
ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings
We present ClusterVO, a stereo Visual Odometry which simultaneously clusters and estimates the motion of both ego and surrounding rigid clusters/objects.
Alternating ConvLSTM: Learning Force Propagation with Alternate State Updates
Experimental results show that Alt-ConvLSTM efficiently models the material kinetic features and greatly outperforms vanilla ConvLSTM with only the single state update.
PCT: Point cloud transformer
It is inherently permutation invariant for processing a sequence of points, making it well-suited for point cloud learning.
Ranked #2 on
3D Point Cloud Classification
on IntrA
Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
Attention mechanisms, especially self-attention, have played an increasingly important role in deep feature representation for visual tasks.
Ranked #16 on
Semantic Segmentation
on PASCAL VOC 2012 test
Recursive-NeRF: An Efficient and Dynamically Growing NeRF
Only query coordinates with high uncertainties are forwarded to the next level to a bigger neural network with a more powerful representational capability.
Can Attention Enable MLPs To Catch Up With CNNs?
In the first week of May, 2021, researchers from four different institutions: Google, Tsinghua University, Oxford University and Facebook, shared their latest work [16, 7, 12, 17] on arXiv. org almost at the same time, each proposing new learning architectures, consisting mainly of linear layers, claiming them to be comparable, or even superior to convolutional-based models.
Subdivision-Based Mesh Convolution Networks
Meshes with arbitrary connectivity can be remeshed to have Loop subdivision sequence connectivity via self-parameterization, making SubdivNet a general approach.
Attention Mechanisms in Computer Vision: A Survey
Humans can naturally and effectively find salient regions in complex scenes.
CIRCLE: Convolutional Implicit Reconstruction and Completion for Large-scale Indoor Scene
We present CIRCLE, a framework for large-scale scene completion and geometric refinement based on local implicit signed distance functions.
ClusterGNN: Cluster-based Coarse-to-Fine Graph Neural Network for Efficient Feature Matching
Graph Neural Networks (GNNs) with attention have been successfully applied for learning visual feature matching.
MonoNeuralFusion: Online Monocular Neural 3D Reconstruction with Geometric Priors
This paper introduces a novel neural implicit scene representation with volume rendering for high-fidelity online 3D scene reconstruction from monocular videos.
Long Range Pooling for 3D Large-Scale Scene Understanding
To achieve the above properties, we propose a simple yet effective long range pooling (LRP) module using dilation max pooling, which provides a network with a large adaptive receptive field.
SLS4D: Sparse Latent Space for 4D Novel View Synthesis
It then learns the spatial features of a 3D position using another sparse latent space.
Semantic-Aware Transformation-Invariant RoI Align
In this paper, we propose a novel RoI feature extractor, termed Semantic RoI Align (SRA), which is capable of extracting invariant RoI features under a variety of transformations for two-stage detectors.
Theoretically Achieving Continuous Representation of Oriented Bounding Boxes
Considerable efforts have been devoted to Oriented Object Detection (OOD).
