
-
Object-Centric Neural Scene Rendering
We present a method for composing photorealistic scenes from captured im...
read it
-
Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection
A common dilemma in 3D object detection for autonomous driving is that h...
read it
-
Virtual Multi-view Fusion for 3D Semantic Segmentation
Semantic segmentation of 3D meshes is an important problem for 3D scene ...
read it
-
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds
Detecting objects in 3D LiDAR data is a core technology for autonomous d...
read it
-
Pillar-based Object Detection for Autonomous Driving
We present a simple and flexible object detection framework optimized fo...
read it
-
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
We propose DOPS, a fast single-stage 3D object detection method for LIDA...
read it
-
3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation
We present 3D-MPA, a method for instance segmentation on 3D point clouds...
read it
-
Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
We propose 4 insights that help to significantly improve the performance...
read it
-
Tracking Emerges by Colorizing Videos
We use large amounts of unlabeled video to learn models for visual track...
read it
-
Instance Embedding Transfer to Unsupervised Video Object Segmentation
We propose a method for unsupervised video object segmentation by transf...
read it
-
The Devil is in the Decoder
Many machine vision applications require predictions for every pixel of ...
read it
-
Semantic Instance Segmentation via Deep Metric Learning
We propose a new method for semantic instance segmentation, by first com...
read it
-
Speed/accuracy trade-offs for modern convolutional object detectors
The goal of this paper is to serve as a guide for selecting a detection ...
read it
-
VideoSET: Video Summary Evaluation through Text
In this paper we present VideoSET, a method for Video Summary Evaluation...
read it
-
An introduction to synchronous self-learning Pareto strategy
In last decades optimization and control of complex systems that possess...
read it
-
A natural-inspired optimization machine based on the annual migration of salmons in nature
Bio inspiration is a branch of artificial simulation science that shows ...
read it