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Found 13 papers, 5 papers with code
Triple Point Masking
Existing 3D mask learning methods encounter performance bottlenecks under limited data, and our objective is to overcome this limitation.
Fast and Efficient: Mask Neural Fields for 3D Scene Segmentation
Recent advancements in distilling 2D vision-language foundation models into neural fields, like NeRF and 3DGS, enable open-vocabulary segmentation of 3D scenes from 2D multi-view images without the need for precise 3D annotations.
Technique Report of CVPR 2024 PBDL Challenges
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies.
Edit-Your-Motion: Space-Time Diffusion Decoupling Learning for Video Motion Editing
In the second stage, we shift focus on learning the appearance features of the source video.
Unveiling and Mitigating Generalized Biases of DNNs through the Intrinsic Dimensions of Perceptual Manifolds
Building fair deep neural networks (DNNs) is a crucial step towards achieving trustworthy artificial intelligence.
Inlier Confidence Calibration for Point Cloud Registration
Firstly we provide finely initial correspondences for ICC in order to generate high quality reference point cloud copy corresponding to the source point cloud.
M3SOT: Multi-frame, Multi-field, Multi-space 3D Single Object Tracking
3D Single Object Tracking (SOT) stands a forefront task of computer vision, proving essential for applications like autonomous driving.
Predicting and Enhancing the Fairness of DNNs with the Curvature of Perceptual Manifolds
To address the challenges of long-tailed classification, researchers have proposed several approaches to reduce model bias, most of which assume that classes with few samples are weak classes.
Ranked #19 on
Long-tail Learning
on CIFAR-10-LT (ρ=10)
Evolutionary Multitasking with Solution Space Cutting for Point Cloud Registration
However, most evolving registration methods cannot tackle the local optimum well and they have rarely investigated the success ratio, which implies the probability of not falling into local optima and is closely related to the practicality of the algorithm.
Multi-view Point Cloud Registration based on Evolutionary Multitasking with Bi-Channel Knowledge Sharing Mechanism
The modeling of multi-view point cloud registration as multi-task optimization are twofold.
A new upper bound and optimal constructions of equi-difference conflict-avoiding codes on constant weight
The size of a CAC is the number of potential users that can be supported in the system.
Information Theory Information Theory
A Light-Weighted Convolutional Neural Network for Bitemporal SAR Image Change Detection
We verify our light-weighted neural network on four sets of bitemporal SAR images.
Two families of Entanglement-assisted quantum MDS codes from constacyclic codes
Entanglement-assisted quantum error correcting codes (EAQECCs) can be derived from arbitrary classical linear codes.
Information Theory Information Theory
