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04/26/2023
PVP: Pre-trained Visual Parameter-Efficient Tuning
Large-scale pre-trained transformers have demonstrated remarkable succes...
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04/03/2023
Small but Mighty: Enhancing 3D Point Clouds Semantic Segmentation with U-Next Framework
We study the problem of semantic segmentation of large-scale 3D point cl...
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03/13/2023
Backdoor Defense via Deconfounded Representation Learning
Deep neural networks (DNNs) are recently shown to be vulnerable to backd...
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10/08/2022
Hierarchical Graph Transformer with Adaptive Node Sampling
The Transformer architecture has achieved remarkable success in a number...
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09/14/2022
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction
Self-supervised depth learning from monocular images normally relies on ...
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04/25/2022
4DAC: Learning Attribute Compression for Dynamic Point Clouds
With the development of the 3D data acquisition facilities, the increasi...
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03/30/2022
Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point Clouds
Sampling is a key operation in point-cloud task and acts to increase com...
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03/21/2022
Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds
We study the problem of efficient object detection of 3D LiDAR point clo...
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03/21/2022
No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces
Scene flow is a powerful tool for capturing the motion field of 3D point...
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03/17/2022
3DAC: Learning Attribute Compression for Point Clouds
We study the problem of attribute compression for large-scale unstructur...
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03/17/2022
STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset
Although various 3D datasets with different functions and scales have be...
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01/09/2022
Box2Seg: Learning Semantics of 3D Point Clouds with Box-Level Supervision
Learning dense point-wise semantics from unstructured 3D point clouds wi...
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11/25/2021
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
Satellite video cameras can provide continuous observation for a large-s...
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11/24/2020
SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration
Extracting robust and general 3D local features is key to downstream tas...
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09/07/2020
Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
An essential prerequisite for unleashing the potential of supervised dee...
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08/05/2020
Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs
To have a better understanding and usage of Convolution Neural Networks ...
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12/27/2019
Deep Learning for 3D Point Clouds: A Survey
Point cloud learning has lately attracted increasing attention due to it...
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11/25/2019
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
We study the problem of efficient semantic segmentation for large-scale ...
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06/04/2019