Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
P2ANet: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos
While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos is still challenging. In this work, we …
Action DetectionAction LocalizationAction RecognitionVideo ClassificationIntelligent 3D Network Protocol for Multimedia Data Classification using Deep Learning
In videos, the human's actions are of three-dimensional (3D) signals. These videos investigate the spatiotemporal knowledge of human behavior. The promising ability is investigated using 3D convolution neural networks (C…
Action RecognitionDeep LearningVideo ClassificationContrastive Self-Supervised Learning Leads to Higher Adversarial Susceptibility
Contrastive self-supervised learning (CSL) has managed to match or surpass the performance of supervised learning in image and video classification. However, it is still largely unknown if the nature of the representatio…
Adversarial RobustnessSelf-Supervised LearningSensitivityVideo ClassificationExploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset
We present a new benchmark dataset, Sapsucker Woods 60 (SSW60), for advancing research on audiovisual fine-grained categorization. While our community has made great strides in fine-grained visual categorization on image…
Fine-Grained Visual CategorizationVideo ClassificationNSNet: Non-saliency Suppression Sampler for Efficient Video Recognition
It is challenging for artificial intelligence systems to achieve accurate video recognition under the scenario of low computation costs. Adaptive inference based efficient video recognition methods typically preview vide…
Action RecognitionVideo ClassificationVideo RecognitionInductive and Transductive Few-Shot Video Classification via Appearance and Temporal Alignments
We present a novel method for few-shot video classification, which performs appearance and temporal alignments. In particular, given a pair of query and support videos, we conduct appearance alignment via frame-level fea…
General ClassificationVideo ClassificationTemporal and cross-modal attention for audio-visual zero-shot learning
Audio-visual generalised zero-shot learning for video classification requires understanding the relations between the audio and visual information in order to be able to recognise samples from novel, previously unseen cl…
GZSL Video ClassificationVideo ClassificationZero-Shot LearningGOCA: Guided Online Cluster Assignment for Self-Supervised Video Representation Learning
Clustering is a ubiquitous tool in unsupervised learning. Most of the existing self-supervised representation learning methods typically cluster samples based on visually dominant features. While this works well for imag…
Action RecognitionClusteringOptical Flow EstimationRepresentation Learning+4Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models
Utilizing vision and language models (VLMs) pre-trained on large-scale image-text pairs is becoming a promising paradigm for open-vocabulary visual recognition. In this work, we extend this paradigm by leveraging motion …
Optical Flow EstimationVideo ClassificationZero-Shot Action RecognitionLong-term Leap Attention, Short-term Periodic Shift for Video Classification
Video transformer naturally incurs a heavier computation burden than a static vision transformer, as the former processes $T$ times longer sequence than the latter under the current attention of quadratic complexity $(T^…
Video ClassificationBeyond Transfer Learning: Co-finetuning for Action Localisation
Transfer learning is the predominant paradigm for training deep networks on small target datasets. Models are typically pretrained on large ``upstream'' datasets for classification, as such labels are easy to collect, an…
Transfer LearningVideo ClassificationPatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the Patch
Adversarial patch attacks mislead neural networks by injecting adversarial pixels within a local region. Patch attacks can be highly effective in a variety of tasks and physically realizable via attachment (e.g. a sticke…
Diversityimage-classificationImage Classificationobject-detection+3Revisiting Classifier: Transferring Vision-Language Models for Video Recognition
Transferring knowledge from task-agnostic pre-trained deep models for downstream tasks is an important topic in computer vision research. Along with the growth of computational capacity, we now have open-source vision-la…
Action ClassificationAction RecognitionClassificationLanguage Modelling+3Key-frame Guided Network for Thyroid Nodule Recognition using Ultrasound Videos
Ultrasound examination is widely used in the clinical diagnosis of thyroid nodules (benign/malignant). However, the accuracy relies heavily on radiologist experience. Although deep learning techniques have been investiga…
Video ClassificationAutomatic Concept Extraction for Concept Bottleneck-based Video Classification
Recent efforts in interpretable deep learning models have shown that concept-based explanation methods achieve competitive accuracy with standard end-to-end models and enable reasoning and intervention about extracted hi…
ClassificationVideo ClassificationAnalysis and Extensions of Adversarial Training for Video Classification
Adversarial training (AT) is a simple yet effective defense against adversarial attacks to image classification systems, which is based on augmenting the training set with attacks that maximize the loss. However, the eff…
Action RecognitionAdversarial DefenseAdversarial RobustnessClassification+3Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs
To build an artificial neural network like the biological intelligence system, recent works have unified numerous tasks into a generalist model, which can process various tasks with shared parameters and do not have any …
Image CaptioningImage ClassificationImage-to-Text RetrievalMixture-of-Experts+5Learning Muti-expert Distribution Calibration for Long-tailed Video Classification
Most existing state-of-the-art video classification methods assume that the training data obey a uniform distribution. However, video data in the real world typically exhibit an imbalanced long-tailed class distribution,…
Classificationimage-classificationImage ClassificationVideo ClassificationConvex Combination Consistency between Neighbors for Weakly-supervised Action Localization
Weakly-supervised temporal action localization (WTAL) intends to detect action instances with only weak supervision, e.g., video-level labels. The current~\textit{de facto} pipeline locates action instances by thresholdi…
Action LocalizationData AugmentationTemporal Action LocalizationVideo Classification+2VPAI_Lab at MedVidQA 2022: A Two-Stage Cross-modal Fusion Method for Medical Instructional Video Classification
This paper introduces the approach of VPAI_Lab team’s experiments on BioNLP 2022 shared task 1 Medical Video Classification (MedVidCL). Given an input video, the MedVidCL task aims to correctly classify it into one of th…
Video Classification