Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Overview of the MedVidQA 2022 Shared Task on Medical Video Question-Answering
In this paper, we present an overview of the MedVidQA 2022 shared task, collocated with the 21st BioNLP workshop at ACL 2022. The shared task addressed two of the challenges faced by medical video question answering: (I)…
Question AnsweringVideo ClassificationVideo Question AnsweringVideo UnderstandingAttention in Attention: Modeling Context Correlation for Efficient Video Classification
Attention mechanisms have significantly boosted the performance of video classification neural networks thanks to the utilization of perspective contexts. However, the current research on video attention generally focuse…
Video ClassificationCalibrating Class Weights with Multi-Modal Information for Partial Video Domain Adaptation
Assuming the source label space subsumes the target one, Partial Video Domain Adaptation (PVDA) is a more general and practical scenario for cross-domain video classification problems. The key challenge of PVDA is to mit…
Domain AdaptationVideo ClassificationSOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition
Learning an egocentric action recognition model from video data is challenging due to distractors (e.g., irrelevant objects) in the background. Further integrating object information into an action model is hence benefic…
Action RecognitionObjectSelf-Supervised LearningVideo ClassificationLong Movie Clip Classification with State-Space Video Models
Most modern video recognition models are designed to operate on short video clips (e.g., 5-10s in length). Thus, it is challenging to apply such models to long movie understanding tasks, which typically require sophistic…
ClassificationDecoderGPUVideo Classification+2StyleFool: Fooling Video Classification Systems via Style Transfer
Video classification systems are vulnerable to adversarial attacks, which can create severe security problems in video verification. Current black-box attacks need a large number of queries to succeed, resulting in high …
Adversarial AttackClassificationDenoisingStyle Transfer+1Alignment-Uniformity aware Representation Learning for Zero-shot Video Classification
Most methods tackle zero-shot video classification by aligning visual-semantic representations within seen classes, which limits generalization to unseen classes. To enhance model generalizability, this paper presents an…
Representation LearningVideo ClassificationZero-Shot Action RecognitionSemi-supervised and Deep learning Frameworks for Video Classification and Key-frame Identification
Automating video-based data and machine learning pipelines poses several challenges including metadata generation for efficient storage and retrieval and isolation of key-frames for scene understanding tasks. In this wor…
RetrievalScene UnderstandingVideo ClassificationUnsupervised Pre-training for Temporal Action Localization Tasks
Unsupervised video representation learning has made remarkable achievements in recent years. However, most existing methods are designed and optimized for video classification. These pre-trained models can be sub-optimal…
Action LocalizationContrastive LearningRepresentation LearningTemporal Action Localization+3Transformers Meet Visual Learning Understanding: A Comprehensive Review
Dynamic attention mechanism and global modeling ability make Transformer show strong feature learning ability. In recent years, Transformer has become comparable to CNNs methods in computer vision. This review mainly inv…
image-classificationImage ClassificationImage Segmentationobject-detection+4Movie Genre Classification by Language Augmentation and Shot Sampling
Video-based movie genre classification has garnered considerable attention due to its various applications in recommendation systems. Prior work has typically addressed this task by adapting models from traditional video…
Action RecognitionBoundary DetectionClassificationEvent Detection+4RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression
Video compression plays a crucial role in video streaming and classification systems by maximizing the end-user quality of experience (QoE) at a given bandwidth budget. In this paper, we conduct the first systematic stud…
Adversarial AttackClassificationDenoisingVideo Classification+2TFCNet: Temporal Fully Connected Networks for Static Unbiased Temporal Reasoning
Temporal Reasoning is one important functionality for vision intelligence. In computer vision research community, temporal reasoning is usually studied in the form of video classification, for which many state-of-the-art…
Action RecognitionClassificationVideo ClassificationVideo Object TrackingRecent Trends in 2D Object Detection and Applications in Video Event Recognition
Object detection serves as a significant step in improving performance of complex downstream computer vision tasks. It has been extensively studied for many years now and current state-of-the-art 2D object detection tech…
2D Object DetectionObjectobject-detectionObject Detection+1A Dataset for Medical Instructional Video Classification and Question Answering
This paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language questions. We believe medical videos may pr…
ClassificationQuestion AnsweringVideo ClassificationVideo UnderstandingLearning To Recognize Procedural Activities with Distant Supervision
In this paper we consider the problem of classifying fine-grained, multi-step activities (e.g., cooking different recipes, making disparate home improvements, creating various forms of arts and crafts) from long videos s…
Action ClassificationLanguage ModellingVideo ClassificationCapturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition
We address the problem of capturing temporal information for video classification in 2D networks, without increasing their computational cost. Existing approaches focus on modifying the architecture of 2D networks (e.g. …
Action RecognitionOptical Flow EstimationVideo ClassificationVideo UnderstandingUniFormer: Unifying Convolution and Self-attention for Visual Recognition
It is a challenging task to learn discriminative representation from images and videos, due to large local redundancy and complex global dependency in these visual data. Convolution neural networks (CNNs) and vision tran…
Image Classificationobject-detectionObject DetectionPose Estimation+3Progressive Video Summarization via Multimodal Self-supervised Learning
Modern video summarization methods are based on deep neural networks that require a large amount of annotated data for training. However, existing datasets for video summarization are small-scale, easily leading to over-…
Self-Supervised LearningSupervised Video SummarizationVideo ClassificationVideo SummarizationCo-training Transformer with Videos and Images Improves Action Recognition
In learning action recognition, models are typically pre-trained on object recognition with images, such as ImageNet, and later fine-tuned on target action recognition with videos. This approach has achieved good empiric…
Action ClassificationAction RecognitionAction Recognition In VideosObject Recognition+1