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20102024
most citedSkeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning

32 citations · 256 across the 40 of their papers we have counts for

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12 papers · 1 filter

cs.CV2023

Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action Recognition

Ming-Zhe Li, Zhen Jia, Zhang Zhang +2

Generalized zero-shot skeleton-based action recognition (GZSSAR) is a new challenging problem in computer vision community, which requires models to recognize actions without any t…

cs.CV2023

Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark

Andong Lu, Zhang Zhang, Yan Huang +4

Nighttime person Re-ID (person re-identification in the nighttime) is a very important and challenging task for visual surveillance but it has not been thoroughly investigated. Und…

cs.CV2023

EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices

Liang Wang, Nan Zhang, Xiaoyang Qu +6

Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewe…

cs.CV2023★ 1 cited

Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning

Liang Wang, Kai Lu, Nan Zhang +5

This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video of changing scenes. Shoggoth uses online kno…

cs.CV2023

Improving Weakly Supervised Temporal Action Localization by Bridging Train-Test Gap in Pseudo Labels

Jingqiu Zhou, Linjiang Huang, Liang Wang +2

The task of weakly supervised temporal action localization targets at generating temporal boundaries for actions of interest, meanwhile the action category should also be classifie…

cs.CV2022

Joint Super-Resolution and Inverse Tone-Mapping: A Feature Decomposition Aggregation Network and A New Benchmark

Gang Xu, Yu-chen Yang, Liang Wang +2

Joint Super-Resolution and Inverse Tone-Mapping (joint SR-ITM) aims to increase the resolution and dynamic range of low-resolution and standard dynamic range images. Recent network…