Search Results for author:
Found 9 papers, 7 papers with code
SlaBins: Fisheye Depth Estimation using Slanted Bins on Road Environments
Based on the slanted MCI, we estimate a set of adaptive bins and a per-pixel probability map for depth estimation.
BAAM: Monocular 3D Pose and Shape Reconstruction With Bi-Contextual Attention Module and Attention-Guided Modeling
A novel monocular 3D pose and shape reconstruction algorithm, based on bi-contextual attention and attention-guided modeling (BAAM), is proposed in this work.
Ranked #1 on
Autonomous Vehicles
on ApolloCar3D
Self-Supervised Surround-View Depth Estimation with Volumetric Feature Fusion
We present a self-supervised depth estimation approach using a unified volumetric feature fusion for surround-view images.
Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes
Second, we generate a set of lane candidates by clustering the training lanes in the eigenlane space.
Ranked #28 on
Lane Detection
on TuSimple
Harmonious Semantic Line Detection via Maximal Weight Clique Selection
A novel algorithm to detect an optimal set of semantic lines is proposed in this work.
Ranked #1 on
Line Detection
on SEL
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 #16 on
Domain Adaptation
on VisDA2017
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample.
End-to-end Learning of Image based Lane-Change Decision
We propose an image based end-to-end learning framework that helps lane-change decisions for human drivers and autonomous vehicles.
Progressive Tree-like Curvilinear Structure Reconstruction with Structured Ranking Learning and Graph Algorithm
We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised learning and graph theory.
