Search Results for author:
Found 14 papers, 5 papers with code
PARSE: An Efficient Search Method for Black-box Adversarial Text Attacks
Previous works on word-level attacks widely use word importance ranking (WIR) methods and complex search methods, including greedy search and heuristic algorithms, to find optimal substitutions.
Flexible 3D Lane Detection by Hierarchical Shape MatchingFlexible 3D Lane Detection by Hierarchical Shape Matching
As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict demands for precision.
MAPLM: A Real-World Large-Scale Vision-Language Benchmark for Map and Traffic Scene Understanding
Specifically we annotate and leverage large-scale broad-coverage traffic and map data extracted from huge HD map annotations and use CLIP and LLaMA-2 / Vicuna to finetune a baseline model with instruction-following data.
A Survey on Multimodal Large Language Models for Autonomous Driving
We first introduce the background of Multimodal Large Language Models (MLLMs), the multimodal models development using LLMs, and the history of autonomous driving.
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels.
LATR: 3D Lane Detection from Monocular Images with Transformer
On the one hand, each query is generated based on 2D lane-aware features and adopts a hybrid embedding to enhance lane information.
Ranked #3 on
3D Lane Detection
on OpenLane
Unbiased estimators for the Heston model with stochastic interest rates
We combine the unbiased estimators in Rhee and Glynn (Operations Research: 63(5), 1026-1043, 2015) and the Heston model with stochastic interest rates.
THMA: Tencent HD Map AI System for Creating HD Map Annotations
THMA has been deployed by the Tencent Map team to provide services to downstream companies and users, serving over 1, 000 labeling workers and producing more than 30, 000 kilometers of HD map data per day at most.
M$^2$-3DLaneNet: Exploring Multi-Modal 3D Lane Detection
Estimating accurate lane lines in 3D space remains challenging due to their sparse and slim nature.
Ranked #10 on
3D Lane Detection
on OpenLane
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
As camera and LiDAR sensors capture complementary information used in autonomous driving, great efforts have been made to develop semantic segmentation algorithms through multi-modality data fusion.
Ranked #4 on
Robust 3D Semantic Segmentation
on nuScenes-C
Density-Based Clustering with Kernel Diffusion
Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC.
Multi-Lead ECG Classification via an Information-Based Attention Convolutional Neural Network
Models embedded with the channel-wise attention structure always achieve better scores on sensitivity and precision than the plain Resnet models.
A hierarchical fusion framework integrating random projection-based classifiers: application in head and neck squamous carcinoma cancer
Ensemble methods achieves better performance than single classifier model.
End-to-End Breast Mass Classification on Digital Breast Tomosynthesis
Automatic classification of the masses in digital breast tomosynthesis(DBT) is still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we develop a End-to-End multi-scale multi-level features fusion Network (EMMFFN) model for breast mass classication using DBT.
