adaptive object detectionkeypoint detectionon-board robot visionvisual wordslifting complex wavelet transformsThis paper proposes a novel method to detect objects by a mobile robot which adapts to an environment
论文笔记:A Robust Learning Approach to Domain Adaptive Object Detection 论文地址:https://ieeexplore.ieee.org/document/9008383 源码地址:https://github.com/Gabriel-Macias/robust_frcnn 1 以前的方法 在目标域中有监督地fine-tuning /无监督地学习跨域表征。前者需要额外的带标签实例数据,后者消除了两个新....
Code for CVPR-22 paper "Towards Robust Adaptive Object Detection under Noisy Annotations"1. IntroductionExisting methods assume that the source domain labels are completely clean, yet large-scale datasets often contain error-prone annotations due to instance ambiguity, which may lead to a biased sourc...
Currently, acquiring multiphoton image still faces challenges, primarily due to the high academic value of multiphoton datasets and legal or ethical constraints involving human samples. It is worth noting that the rapid development of computer vision is closely related to the open-source and large-sca...
Multimodal Inplace Prompt Tuning for Open-set Object Detection 2024, MM 2024 - Proceedings of the 32nd ACM International Conference on Multimedia PASS: Pruning Attention Heads with Almost-sure Sparsity Targets 2024, Transactions on Machine Learning Research Application of the Lightweight BERT Model for...
A norm calibration layer and an adaptive multi-feature selection strategy which is based on the per-level losses are proposed and studied. The proposed NCMS significantly improves strong baseline and achieves competitive results to the state-of-the-art single-stage model. CRediT authorship ...
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection Junjie Yan Yingfei Liu ✉ Jianjian Sun Fan Jia Tiancai Wang Xiangyu Zhang MEGVII Technology Shuailin Li Abstract In this paper, we propose a robust 3D detector, named Cross Modal Transformer (CMT...
Domain Adaptive Faster R-CNN for Object Detection in the Wild, CVPR'18 (Our re-implementation) (link) Data preparation We have included the following set of datasets for our implementation: CitysScapes, FoggyCityscapes: Download websiteCityscapes, see dataset preparation code inDA-Faster RCNN ...
The results demonstrate that the mean Average Precision (mAP) of our proposed MwdpNet on the four datasets achieve 87.0%, 89.2%, 78.3%, and 76.0%, respectively, outperforming nine mainstream object detection algorithms. Our proposed approach provides an effective means and strategy for detecting ...
AdaScale: Towards real-time video object detection using adaptive scaling 2019-02-18 16:14:17 Paper:https://www.sysml.cc/papers.html 本文提出一种新的技术,AdaScale,来改善视频中物体检测的尺度问题,在提升速度的同时,改善了精度。 作者的实验发现在降低图像分辨率的时候,部分图像的识别精度就会得到改善,并...