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Found 12 papers, 8 papers with code
Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting
One promising self-supervised task is 3D point cloud forecasting from unannotated LiDAR sequences.
Differentiable Raycasting for Self-supervised Occupancy Forecasting
Self-supervised representations proposed for large-scale planning, such as ego-centric freespace, confound these two motions, making the representation difficult to use for downstream motion planners.
Safe Local Motion Planning With Self-Supervised Freespace Forecasting
Finally, we propose future freespace as an additional source of annotation-free supervision.
Active Perception using Light Curtains for Autonomous Driving
Most real-world 3D sensors such as LiDARs perform fixed scans of the entire environment, while being decoupled from the recognition system that processes the sensor data.
Inferring Distributions Over Depth from a Single Image
Such approaches cannot diagnose when failures might occur.
What You See is What You Get: Exploiting Visibility for 3D Object Detection
On the NuScenes 3D detection benchmark, we show that, by adding an additional stream for visibility input, we can significantly improve the overall detection accuracy of a state-of-the-art 3D detector.
Learning to Optimally Segment Point Clouds
We prove that if we score a segmentation by the worst objectness among its individual segments, there is an efficient algorithm that finds the optimal worst-case segmentation among an exponentially large number of candidate segmentations.
Active Learning with Partial Feedback
While many active learning papers assume that the learner can simply ask for a label and receive it, real annotation often presents a mismatch between the form of a label (say, one among many classes), and the form of an annotation (typically yes/no binary feedback).
Unconstrained Face Detection and Open-Set Face Recognition Challenge
Face detection and recognition benchmarks have shifted toward more difficult environments.
Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset
Person detection from vehicles has made rapid progress recently with the advent of multiple highquality datasets of urban and highway driving, yet no large-scale benchmark is available for the same problem in off-road or agricultural environments.
Finding Tiny Faces
We explore three aspects of the problem in the context of finding small faces: the role of scale invariance, image resolution, and contextual reasoning.
Ranked #25 on
Face Detection
on WIDER Face (Medium)
Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians
We show that RGs can be optimized with a quadratic program (QP), that can in turn be optimized with a recurrent neural network (with rectified linear units).
Ranked #40 on
Pose Estimation
on MPII Human Pose
