Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Efficient Movie Scene Detection using State-Space Transformers
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 RecognitionTruncate-Split-Contrast: A Framework for Learning from Mislabeled Videos
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 ClassificationVideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners
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+7Evaluation of Explanation Methods of AI -- CNNs in Image Classification Tasks with Reference-based and No-reference Metrics
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 ClassificationA Unified Multimodal De- and Re-coupling Framework for RGB-D Motion Recognition
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 ClassificationDeep Unsupervised Key Frame Extraction for Efficient Video Classification
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 ClassificationBOREx: Bayesian-Optimization--Based Refinement of Saliency Map for Image- and Video-Classification Models
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 ClassificationTransfer-learning for video classification: Video Swin Transformer on multiple domains
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 ClassificationLinear Video Transformer with Feature Fixation
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 ClassificationOverlooked Video Classification in Weakly Supervised Video Anomaly Detection
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+2S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces
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 ClassificationTAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video Surveillance
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+1FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classification
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 ClassificationTraffic Congestion Prediction using Deep Convolutional Neural Networks: A Color-coding Approach
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 ClassificationOn the Surprising Effectiveness of Transformers in Low-Labeled Video Recognition
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+1UAV-CROWD: Violent and non-violent crowd activity simulator from the perspective of UAV
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 ClassificationMotion Sensitive Contrastive Learning for Self-supervised Video Representation
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+2Two-Stream Transformer Architecture for Long Video Understanding
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+2SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized Violence
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+1Adaptive occlusion sensitivity analysis for visually explaining video recognition networks
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