CO-MOT:end-to-end tracking也能SOTA。简单易用,性能拔群 颜丙峰 为生活奔波的人 来自专栏 · 多摄像头下多目标跟踪(MCMT) 24 人赞同了该文章 万众瞩目!智能辅助助力e2e-MOT,全新Co-MOT横空出世!它突破了e2e-MOT的束缚,创新性地提出了基于合作竞争(COopetition)的标签分配策略,并引入影子概念,让检测query与追踪q
— from RTLS hardware to customized applications — Traceability Collect and manage information about the manufacturing processes from raw material input to shipment of products. Fleet tracking and control Analyze and optimize the activity of your fork lifts and other logistic devices on the shopfloor ...
摘要 跟踪通常采用特征提取、目标信息集成和包围盒估计的多级流程。为了简化这一流程,并统一特征提取和目标信息集成的过程,我们提出了一个紧凑的跟踪框架,称为MixFormer。我们的核心设计是利用注意力操作的灵活…
End-to-end order trackingThe article announces that Surface Technology International possesses a manufacturing execution system that allows its customers to monitor orders using their smartphones highlighting the views of director of operations Chris Lyon on the system.Electronics Weekly...
MOTR: End-to-End Multiple-Object Tracking with Transformer link 时间:22.07 机构:Megvii TL;DR 传统MOT通过motion与appearance来建模,有复杂的后处理难以E2E。本文基于DETR设计出MOTR算法,通过
BERT-DST: Scalable End-to-End Dialogue State Tracking with Bidirectional Encoder Representations from Transformer 概要 问题动机 对话状态跟踪 (DST) 中一个重要但很少被解决的问题是动态 ontology(如电影、餐馆)和 unseen 的插槽值的可扩展性。以前的方法通常依赖于 n 格枚举或槽标记输出的候选生成,这可能遭受...
MixFormer is composed of atarget-search mixed attention (MAM) based backboneand a simple corner head, yielding a compact tracking pipeline without an explicit integration module. ✨ End-to-end, post-processing-free Mixformer is an end-to-end tracking framework without post-processing. ...
MOTR : Multi-Object Tracking with tRansformers MOTR is a simple online tracker. It is easy to develop based on DETR with minor modifications on label assignment. MOTR modifies the object query input in DETR to track queries, which corresponds to tracks of objects in a video. It does that wi...
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代码:https://github.com/megvii-research/MOTR 博客解读:https://www.zjp97.top/tracking/62-MOTR/ MOTR是基于Transformer的MOT,是第一个真正严格意义上端到端的多目标跟踪框架,超越了此前的TransTrack和TrackFormer等工作。 Motivation 时域建模是MOT的关键挑战,现有方法通过运动和外观相似度来关联检测结果进行跟踪。