In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end multi-object tracking with pretrained object detector. Existing methods, e.g. MOTR [43] and TrackFormer [20] are inferior their tracking-by-detection counterparts mainly due poor detection performance. We aim improve by elegantly incorporating an extra first adopt the anchor formulation of queries then use detector generate proposals as anchors, providing prior MOTR. The modification greatly eases...

In this paper, we propose a new query-based detection framework for crowd detection. Previous detectors suffer from two drawbacks: first, multiple predictions will be inferred single object, typically in crowded scenes; second, the performance saturates as depth of decoding stage increases. Benefiting nature one-to-one label assignment rule, progressive predicting method to address above issues. Specifically, first select accepted queries prone generate true positive predictions, then refine...

Emotion recognition has become an important component of human–computer interaction systems. Research on emotion based electroencephalogram (EEG) signals are mostly conducted by the analysis all channels' EEG signals. Although some progresses achieved, there still several challenges such as high dimensions, correlation between different features and feature redundancy in realistic experimental process. These have hindered applications to portable systems (or devices). This paper explores how...

Referring video object segmentation (RVOS) aims at segmenting an in a following human instruction. Current state-of-the-art methods fall into offline pattern, which each clip independently interacts with text embedding for cross-modal understanding. They usually present that the pattern is necessary RVOS, yet model limited temporal association within clip. In this work, we break up previous belief and propose simple effective online using explicit query propagation, named OnlineRefer....

Colorization is a traditional computer vision task and it plays an important role in many time-consuming tasks, such as old film restoration. Existing methods suffer from unsaturated color temporally inconsistency. In this paper, we propose novel pipeline to overcome the challenges. We regard colorization generative introduce Stable Video Diffusion (SVD) our base model. design palette-based guider assist model generating vivid consistent colors. The context introduced by palette not only...

Pedestrian detection in a crowd is challenging task due to high number of mutually-occluding human instances, which brings ambiguity and optimization difficulties the current IoU-based ground truth assignment procedure classical object methods. In this paper, we develop unique perspective pedestrian as variational inference problem. We formulate novel efficient algorithm for by modeling dense proposals latent variable while proposing customized Auto-Encoding Variational Bayes (AEVB)...

With the development of Vehicular Ad-hoc Networks (VANETs), several data security challenges are revealed, such as hijacking and interception. Although vehicles authorized, malicious behaviors still be carried out. Security lapses may lead to potential accidents, which emphasizes importance laying a solid foundation for VANETs. Thanks base layer provided by cryptography technologies, problems can solved in VANETs avoid accidents. However, trust management focuses on analysis identification...

Abstract Objective . Emotion recognition on the basis of electroencephalography (EEG) signals has received a significant amount attention in areas cognitive science and human–computer interaction (HCI). However, most existing studies either focus one-dimensional EEG data, ignoring relationship between channels, or only extract time–frequency features while not involving spatial features. Approach We develop spatial–temporal features-based emotion using graph convolution network (GCN) long...

Although the existing networks are more often deployed in multidomain environment, most of researches focus on single-domain and there no appropriate solutions for virtual network mapping problem. In fact, studies assume that underlying can operate without any interruption. However, physical cannot ensure normal provision services external reasons traditional have difficulties to meet user needs, especially high security requirements transmission. order solve above problems, this paper...

Eye blinks take an important role for electroencephalography (EEG) signals that on one hand, they can severely impact the EEG signals, and other may provide useful information brain–computer interface (BCI) scientific applications. In particular, it is challenging to detect in real time from a single channel of signals. this work, we propose short windowed random forest based method toward Real-Time Blink detection (RT-Blink), which balances processing granularity computation complexity....

Although end-to-end multi-object trackers like MOTR enjoy the merits of simplicity, they suffer from conflict between detection and association seriously, resulting in unsatisfactory convergence dynamics. While MOTRv2 partly addresses this problem, it demands an additional network for assistance. In work, we serve as first to reveal that arises unfair label assignment detect queries track during training, where these recognize targets associate them. Based on observation, propose MOTRv3,...

Summary Network virtualization is a promising technology, which used to solve the existing shortcomings of Internet architecture and in virtual network (VN) embedding plays vital role resource allocation. However, current algorithms mainly deal with static VN embedding; allocations resources are constant excessive requests' lifetime. In reality, user's requirements usually change time; hence, can lead low utilization substrate reduction operators' revenues. To aforementioned problem, we...

In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end multi-object tracking with pretrained object detector. Existing methods, MOTR and TrackFormer are inferior their tracking-by-detection counterparts mainly due poor detection performance. We aim improve by elegantly incorporating an extra first adopt the anchor formulation of queries then use detector generate proposals as anchors, providing prior MOTR. The modification greatly eases conflict between...

Referring video object segmentation (RVOS) aims at segmenting an in a following human instruction. Current state-of-the-art methods fall into offline pattern, which each clip independently interacts with text embedding for cross-modal understanding. They usually present that the pattern is necessary RVOS, yet model limited temporal association within clip. In this work, we break up previous belief and propose simple effective online using explicit query propagation, named OnlineRefer....

Haze severely affects the reliability of vision-based industrial systems, and most current dehazing methods are not applicable to images captured by ultra-high-definition (UHD) cameras. In this article, we propose a novel dimensional transformation mixer (DMixer) model for recovering haze-free from UHD haze images. DMixer, module encodes complete image in multiple stages different perspectives associates features views permuting tensor efficient long-range dependency modeling. way, global...

Unsupervised Outlier Detection (UOD) is an important data mining task. With the advance of deep learning, (OD) has received broad interest. Most UOD models are trained exclusively on clean datasets to learn distribution normal data, which requires huge manual efforts real-world if possible. Instead relying datasets, some approaches directly train and detect unlabeled contaminated leading need for methods that robust such conditions. Ensemble emerged as a superior solution enhance model...