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Found 8 papers, 0 papers with code
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations
The fusion of causal models with deep learning introducing increasingly intricate data sets, such as the causal associations within images or between textual components, has surfaced as a focal research area.
A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms
Understanding causality helps to structure interventions to achieve specific goals and enables predictions under interventions.
Reconstruct from BEV: A 3D Lane Detection Approach based on Geometry Structure Prior
Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global.
Multi-level Domain Adaptation for Lane Detection
We focus on bridging domain discrepancy in lane detection among different scenarios to greatly reduce extra annotation and re-training costs for autonomous driving.
Reconstruct from Top View: A 3D Lane Detection Approach based on Geometry Structure Prior
Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global.
Ranked #6 on
3D Lane Detection
on Apollo Synthetic 3D Lane
What Matters In Branch Specialization? Using a Toy Task to Make Predictions
What motivates the brain to allocate tasks to different regions and what distinguishes multiple-demand brain regions and the tasks they perform from ones in highly specialized areas?
Ensuring Readability and Data-fidelity using Head-modifier Templates in Deep Type Description Generation
A type description is a succinct noun compound which helps human and machines to quickly grasp the informative and distinctive information of an entity.
KDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation
We propose KDSL, a new word sense disambiguation (WSD) framework that utilizes knowledge to automatically generate sense-labeled data for supervised learning.
