1.2k citations · 1.6k across the 55 of their papers we have counts for
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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…
The Weighting Game: Evaluating Quality of Explainability Methods
Lassi Raatikainen, Esa Rahtu
The objective of this paper is to assess the quality of explanation heatmaps for image classification tasks. To assess the quality of explainability methods, we approach the task t…
Cascaded and Generalizable Neural Radiance Fields for Fast View Synthesis
Phong Nguyen-Ha, Lam Huynh, Esa Rahtu +2
We present CG-NeRF, a cascade and generalizable neural radiance fields method for view synthesis. Recent generalizing view synthesis methods can render high-quality novel views usi…
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…
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…
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…
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…
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…