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Found 6 papers, 1 papers with code
DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous Driving
In this paper, we propose a Deep Reinforcement Learning (DRL)-based trajectory tracking method for the motion-related modules in autonomous driving systems.
Parameterized Cost Volume for Stereo Matching
In this paper, we propose a parameterized cost volume to encode the entire disparity space using multi-Gaussian distribution.
Sparse Point Guided 3D Lane Detection
The high-resolution local information brought by sparse points refines 3D lanes in the BEV space hierarchically from low resolution to high resolution.
FoggyStereo: Stereo Matching With Fog Volume Representation
Stereo matching in foggy scenes is challenging as the scattering effect of fog blurs the image and makes the matching ambiguous.
Content-Aware Inter-Scale Cost Aggregation for Stereo Matching
In this paper, we present a content-aware inter-scale cost aggregation method that adaptively aggregates and upsamples the cost volume from coarse-scale to fine-scale by learning dynamic filter weights according to the content of the left and right views on the two scales.
Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture
The cost aggregation sub-architecture is realized by a two-stream network: one for the generation of cost aggregation proposals, the other for the selection of the proposals.
