Search Results for author:
Found 10 papers, 6 papers with code
Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem
Typical LiDAR-based 3D object detection models are trained in a supervised manner with real-world data collection, which is often imbalanced over classes (or long-tailed).
PANDAS: Prototype-based Novel Class Discovery and Detection
In this work, we look at ways to extend a detector trained for a set of base classes so it can i) spot the presence of novel classes, and ii) automatically enrich its repertoire to be able to detect those newly discovered classes together with the base ones.
How Does Artificial Intelligence Improve Human Decision-Making? Evidence from the AI-Powered Go Program
We study how humans learn from AI, exploiting an introduction of an AI-powered Go program (APG) that unexpectedly outperformed the best professional player.
TransDSSL: Transformer based Depth Estimation via Self-Supervised Learning
Recently, transformers have been widely adopted for various computer vision tasks and show promising results due to their ability to encode long-range spatial dependencies in an image effectively.
Ranked #3 on
Monocular Depth Estimation
on DDAD
MLPD: Multi-Label Pedestrian Detector in Multispectral Domain
In this letter, we tackle multispectral pedestrian detection, where all input data are not paired.
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation
Recent works on domain adaptation exploit adversarial training to obtain domain-invariant feature representations from the joint learning of feature extractor and domain discriminator networks.
Ranked #15 on
Domain Adaptation
on VisDA2017
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
In this paper, we propose a unified end-to-end trainable multi-task network that jointly handles lane and road marking detection and recognition that is guided by a vanishing point under adverse weather conditions.
Ranked #1 on
Lane Detection
on Caltech Lanes Washington
Fine-scale Surface Normal Estimation using a Single NIR Image
We present surface normal estimation using a single near infrared (NIR) image.
Multispectral Pedestrian Detection: Benchmark Dataset and Baseline
With this dataset, we introduce multispectral ACF, which is an extension of aggregated channel features (ACF) to simultaneously handle color-thermal image pairs.
