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Found 13 papers, 5 papers with code
OmniColor: A Global Camera Pose Optimization Approach of LiDAR-360Camera Fusion for Colorizing Point Clouds
A Colored point cloud, as a simple and efficient 3D representation, has many advantages in various fields, including robotic navigation and scene reconstruction.
NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning
Navigating a nonholonomic robot in a cluttered environment requires extremely accurate perception and locomotion for collision avoidance.
Application of Deep Learning in Blind Motion Deblurring: Current Status and Future Prospects
As a response, blind motion deblurring has emerged, aiming to restore clear and detailed images without prior knowledge of the blur type, fueled by the advancements in deep learning methodologies.
You Do Not Need Additional Priors in Camouflage Object Detection
Camouflage object detection (COD) poses a significant challenge due to the high resemblance between camouflaged objects and their surroundings.
EMEF: Ensemble Multi-Exposure Image Fusion
In the second stage, we tune the imitator network by optimizing the style code, in order to find an optimal fusion result for each input pair.
Position-Aware Relation Learning for RGB-Thermal Salient Object Detection
FRDF utilizes the directional information between object pixels to effectively enhance the intra-class compactness of salient regions.
Federated Deep Learning Meets Autonomous Vehicle Perception: Design and Verification
However, it is challenging to determine the network resources and road sensor placements for multi-stage training with multi-modal datasets in multi-variant scenarios.
PixelGame: Infrared small target segmentation as a Nash equilibrium
FNs-player and FPs-player are designed with different strategies: One is to minimize FNs and the other is to minimize FPs.
BBA-net: A bi-branch attention network for crowd counting
Our method can integrate the pedestrian's head and body information to enhance the feature expression ability of the density map.
Enhancing and Dissecting Crowd Counting By Synthetic Data
In this article, we propose a simulated crowd counting dataset CrowdX, which has a large scale, accurate labeling, parameterized realization, and high fidelity.
Knowledge Distillation with Noisy Labels for Natural Language Understanding
Knowledge Distillation (KD) is extensively used to compress and deploy large pre-trained language models on edge devices for real-world applications.
Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation
To narrow this gap, we propose a network fusion architecture, which consists of a multispectral proposal network to generate pedestrian proposals, and a subsequent multispectral classification network to distinguish pedestrian instances from hard negatives.
Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection
Multispectral images of color-thermal pairs have shown more effective than a single color channel for pedestrian detection, especially under challenging illumination conditions.
