Search Results for author:
Found 7 papers, 4 papers with code
GraphAD: Interaction Scene Graph for End-to-end Autonomous Driving
With the representation of the ISG, the driving agents aggregate essential information from the most influential elements, including the road agents with potential collisions and the map elements to follow.
3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling
We present a novel approach from the perspective of auto-labelling, aiming to generate a large number of 3D scene flow pseudo labels for real-world LiDAR point clouds.
Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection
3D object Detection with LiDAR-camera encounters overfitting in algorithm development which is derived from the violation of some fundamental rules.
Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion
However, due to the inherent representation gap between stereo geometry and BEV features, it is non-trivial to bridge them for dense prediction task of SSC.
Unconstrained Facial Landmark Localization with Backbone-Branches Fully-Convolutional Networks
This paper investigates how to rapidly and accurately localize facial landmarks in unconstrained, cluttered environments rather than in the well segmented face images.
Deep Joint Task Learning for Generic Object Extraction
We present a general joint task learning framework, in which each task (either object localization or object segmentation) is tackled via a multi-layer convolutional neural network, and the two networks work collaboratively to boost performance.
An Expressive Deep Model for Human Action Parsing from A Single Image
This paper aims at one newly raising task in vision and multimedia research: recognizing human actions from still images.
