activity
20172022
most citedImage coding for machines: an end-to-end learned approach

118 citations · 272 across the 20 of their papers we have counts for

collaborators

35 papers

cs.CV20221 cited

SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimation

Dingding Cai, Janne Heikkilä, Esa Rahtu

This paper presents an efficient symmetry-agnostic and correspondence-free framework, referred to as SC6D, for 6D object pose estimation from a single monocular RGB image. SC6D req…

cs.CV2022

OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimation

Dingding Cai, Janne Heikkilä, Esa Rahtu

This paper proposes a universal framework, called OVE6D, for model-based 6D object pose estimation from a single depth image and a target object mask. Our model is trained using pu…

cs.CV2022

Online panoptic 3D reconstruction as a Linear Assignment Problem

Leevi Raivio, Esa Rahtu

Real-time holistic scene understanding would allow machines to interpret their surrounding in a much more detailed manner than is currently possible. While panoptic image segmentat…

cs.CV2022

AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval

Riku Togashi, Mayu Otani, Yuta Nakashima +3

Evaluation measures have a crucial impact on the direction of research. Therefore, it is of utmost importance to develop appropriate and reliable evaluation measures for new applic…

cs.CV2022

Optimal Correction Cost for Object Detection Evaluation

Mayu Otani, Riku Togashi, Yuta Nakashima +3

Mean Average Precision (mAP) is the primary evaluation measure for object detection. Although object detection has a broad range of applications, mAP evaluates detectors in terms o…

cs.CV20222 cited

Fast Neural Architecture Search for Lightweight Dense Prediction Networks

Lam Huynh, Esa Rahtu, Jiri Matas +1

We present LDP, a lightweight dense prediction neural architecture search (NAS) framework. Starting from a pre-defined generic backbone, LDP applies the novel Assisted Tabu Search…