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Found 9 papers, 4 papers with code
Amelia: A Large Model and Dataset for Airport Surface Movement Forecasting
While data-driven methods have shown improvements in these tasks, prior works lack large-scale curated surface movement datasets within the public domain and the development of generalizable trajectory forecasting models.
Importance of negative sampling in weak label learning
Weak-label learning is a challenging task that requires learning from data "bags" containing positive and negative instances, but only the bag labels are known.
CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame
CRIN directly takes the coordinates of points as input and transforms local points into rotation-invariant representations via centrifugal reference frames.
Visualizing Ensemble Predictions of Music Mood
Music mood classification has been a challenging problem in comparison with other music classification problems (e. g., genre, composer, or period).
Multimodal Object Detection via Probabilistic Ensembling
Object detection with multimodal inputs can improve many safety-critical systems such as autonomous vehicles (AVs).
Ranked #2 on
Object Detection
on InOutDoor
Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes
In the work, we disentangle the direct offset into Local Canonical Coordinates (LCC), box scales and box orientations.
Transferable Active Grasping and Real Embodied Dataset
Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects.
3D Objectness Estimation via Bottom-up Regret Grouping
Further ablation study also demonstrates the effectiveness of our grouping predictor and regret mechanism.
TRL: Discriminative Hints for Scalable Reverse Curriculum Learning
However, tasks with sparse rewards remain challenging when the state space is large.
