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Found 8 papers, 1 papers with code
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-Exploration
The diffusion model, a new generative modeling paradigm, has achieved significant success in generating images, audio, video, and text.
GaitTAKE: Gait Recognition by Temporal Attention and Keypoint-guided Embedding
Gait recognition, which refers to the recognition or identification of a person based on their body shape and walking styles, derived from video data captured from a distance, is widely used in crime prevention, forensic identification, and social security.
Package Theft Detection from Smart Home Security Cameras
Package theft detection has been a challenging task mainly due to lack of training data and a wide variety of package theft cases in reality.
NTIRE 2021 Multi-modal Aerial View Object Classification Challenge
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR.
Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment
Radar has long been a common sensor on autonomous vehicles for obstacle ranging and speed estimation.
Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model
In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT) of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based camera link model (TCLM).
Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model
In this paper, we propose an effective and reliable MTMCT framework for vehicles, which consists of a traffic-aware single camera tracking (TSCT) algorithm, a trajectory-based camera link model (CLM) for vehicle re-identification (ReID), and a hierarchical clustering algorithm to obtain the cross camera vehicle trajectories.
IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency
Meanwhile, the spatial attention, which focuses on the foreground within the bounding boxes, is generated from the given instance masks and applied to the extracted embedding features.
