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Papers Video Classification

“Video Classification” 태그가 달린 논문 495편 · 필터 해제

Efficient Movie Scene Detection using State-Space Transformers

2022-12-29 · CVPR 2023 1 · Md Mohaiminul Islam, Mahmudul Hasan, Kishan Shamsundar Athrey, Tony Braskich 외

The ability to distinguish between different movie scenes is critical for understanding the storyline of a movie. However, accurately detecting movie scenes is often challenging as it requires the ability to reason over …

GPUScene SegmentationVideo ClassificationVideo Recognition

Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos

2022-12-27 · Zixiao Wang, Junwu Weng, Chun Yuan, Jue Wang

Learning with noisy label (LNL) is a classic problem that has been extensively studied for image tasks, but much less for video in the literature. A straightforward migration from images to videos without considering the…

channel selectionContrastive LearningVideo Classification

VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners

2022-12-09 · Shen Yan, Tao Zhu, ZiRui Wang, Yuan Cao 외

We explore an efficient approach to establish a foundational video-text model. We present VideoCoCa that maximally reuses a pretrained image-text contrastive captioner (CoCa) model and adapt it to video-text tasks with m…

Question AnsweringRetrievalText to Video RetrievalVideo Captioning+7

Evaluation of Explanation Methods of AI -- CNNs in Image Classification Tasks with Reference-based and No-reference Metrics

2022-12-02 · A. Zhukov, J. Benois-Pineau, R. Giot

The most popular methods in AI-machine learning paradigm are mainly black boxes. This is why explanation of AI decisions is of emergency. Although dedicated explanation tools have been massively developed, the evaluation…

image-classificationImage ClassificationVideo Classification

A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion Recognition

2022-11-16 · Benjia Zhou, Pichao Wang, Jun Wan, Yanyan Liang 외

Motion recognition is a promising direction in computer vision, but the training of video classification models is much harder than images due to insufficient data and considerable parameters. To get around this, some wo…

Action RecognitionData AugmentationRepresentation LearningVideo Classification

Deep Unsupervised Key Frame Extraction for Efficient Video Classification

2022-11-12 · Hao Tang, Lei Ding, Songsong Wu, Bin Ren 외

Video processing and analysis have become an urgent task since a huge amount of videos (e.g., Youtube, Hulu) are uploaded online every day. The extraction of representative key frames from videos is very important in vid…

ClassificationVideo Classification

BOREx: Bayesian-Optimization--Based Refinement of Saliency Map for Image- and Video-Classification Models

2022-10-31 · Atsushi Kikuchi, Kotaro Uchida, Masaki Waga, Kohei Suenaga

Explaining a classification result produced by an image- and video-classification model is one of the important but challenging issues in computer vision. Many methods have been proposed for producing heat-map--based exp…

Bayesian OptimizationClassificationGPRVideo Classification

Transfer-learning for video classification: Video Swin Transformer on multiple domains

2022-10-18 · Daniel A. P. Oliveira, David Martins de Matos

The computer vision community has seen a shift from convolutional-based to pure transformer architectures for both image and video tasks. Training a transformer from zero for these tasks usually requires a lot of data an…

Transfer LearningVideo Classification

Linear Video Transformer with Feature Fixation

2022-10-15 · Kaiyue Lu, Zexiang Liu, Jianyuan Wang, Weixuan Sun 외

Vision Transformers have achieved impressive performance in video classification, while suffering from the quadratic complexity caused by the Softmax attention mechanism. Some studies alleviate the computational costs by…

Feature ImportanceVideo Classification

Overlooked Video Classification in Weakly Supervised Video Anomaly Detection

2022-10-13 · Weijun Tan, Qi Yao, Jingfeng Liu

Current weakly supervised video anomaly detection algorithms mostly use multiple instance learning (MIL) or their varieties. Almost all recent approaches focus on how to select the correct snippets for training to improv…

AllAnomaly DetectionClassificationMultiple Instance Learning+2

S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces

2022-10-12 · Eric Nguyen, Karan Goel, Albert Gu, Gordon W. Downs 외

Visual data such as images and videos are typically modeled as discretizations of inherently continuous, multidimensional signals. Existing continuous-signal models attempt to exploit this fact by modeling the underlying…

Inductive BiasState Space ModelsVideo Classification

TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video Surveillance

2022-09-26 · Yajun Xu, Chuwen Huang, Yibing Nan, Shiguo Lian

Automatic traffic accidents detection has appealed to the machine vision community due to its implications on the development of autonomous intelligent transportation systems (ITS) and importance to traffic safety. Most …

image-classificationImage Classificationobject-detectionObject Detection+1

FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classification

2022-09-22 · Pu Jin, Lichao Mou, Yuansheng Hua, Gui-Song Xia 외

Unmanned aerial vehicles (UAVs) are now widely applied to data acquisition due to its low cost and fast mobility. With the increasing volume of aerial videos, the demand for automatically parsing these videos is surging.…

Action RecognitionTemporal Action LocalizationVideo Classification

Traffic Congestion Prediction using Deep Convolutional Neural Networks: A Color-coding Approach

2022-09-16 · Mirza Fuad Adnan, Nadim Ahmed, Imrez Ishraque, Md. Sifath Al Amin 외

The traffic video data has become a critical factor in confining the state of traffic congestion due to the recent advancements in computer vision. This work proposes a unique technique for traffic video classification u…

Classificationvehicle detectionVideo Classification

On the Surprising Effectiveness of Transformers in Low-Labeled Video Recognition

2022-09-15 · Farrukh Rahman, Ömer Mubarek, Zsolt Kira

Recently vision transformers have been shown to be competitive with convolution-based methods (CNNs) broadly across multiple vision tasks. The less restrictive inductive bias of transformers endows greater representation…

image-classificationImage ClassificationInductive BiasVideo Classification+1

UAV-CROWD: Violent and non-violent crowd activity simulator from the perspective of UAV

2022-08-13 · Mahieyin Rahmun, Tonmoay Deb, Shahriar Ali Bijoy, Mayamin Hamid Raha

Unmanned Aerial Vehicle (UAV) has gained significant traction in the recent years, particularly the context of surveillance. However, video datasets that capture violent and non-violent human activity from aerial point-o…

Semantic SegmentationVideo Classification

Motion Sensitive Contrastive Learning for Self-supervised Video Representation

2022-08-12 · Jingcheng Ni, Nan Zhou, Jie Qin, Qian Wu 외

Contrastive learning has shown great potential in video representation learning. However, existing approaches fail to sufficiently exploit short-term motion dynamics, which are crucial to various down-stream video unders…

Contrastive LearningRepresentation LearningRetrievalVideo Classification+2

Two-Stream Transformer Architecture for Long Video Understanding

2022-08-02 · Edward Fish, Jon Weinbren, Andrew Gilbert

Pure vision transformer architectures are highly effective for short video classification and action recognition tasks. However, due to the quadratic complexity of self attention and lack of inductive bias, transformers …

Action RecognitionGPUInductive BiasVideo Classification+2

SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized Violence

2022-07-26 · Toluwani Aremu, Li Zhiyuan, Reem Alameeri, Mustaqeem Khan 외

Detection of violence and weaponized violence in closed-circuit television (CCTV) footage requires a comprehensive approach. In this work, we introduce the \emph{Smart-City CCTV Violence Detection (SCVD)} dataset, specif…

Action Recognitionimage-classificationImage ClassificationVideo Classification+1

Adaptive occlusion sensitivity analysis for visually explaining video recognition networks

2022-07-26 · Tomoki Uchiyama, Naoya Sogi, Satoshi Iizuka, Koichiro Niinuma 외

This paper proposes a method for visually explaining the decision-making process of video recognition networks with a temporal extension of occlusion sensitivity analysis, called Adaptive Occlusion Sensitivity Analysis (…

Decision Makingimage-classificationImage ClassificationSensitivity+2
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