Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Malicious or Benign? Towards Effective Content Moderation for Children's Videos
Online video platforms receive hundreds of hours of uploads every minute, making manual content moderation impossible. Unfortunately, the most vulnerable consumers of malicious video content are children from ages 1-5 wh…
Video ClassificationAlternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception
We present Integrated Multimodal Perception (IMP), a simple and scalable multimodal multi-task training and modeling approach. IMP integrates multimodal inputs including image, video, text, and audio into a single Transf…
Classificationimage-classificationImage ClassificationMixture-of-Experts+7HateMM: A Multi-Modal Dataset for Hate Video Classification
Hate speech has become one of the most significant issues in modern society, having implications in both the online and the offline world. Due to this, hate speech research has recently gained a lot of traction. However,…
ClassificationHate Speech DetectionVideo ClassificationVerbs in Action: Improving verb understanding in video-language models
Understanding verbs is crucial to modelling how people and objects interact with each other and the environment through space and time. Recently, state-of-the-art video-language models based on CLIP have been shown to ha…
Contrastive LearningQuestion AnsweringText MatchingVideo Classification+2SparseFormer: Sparse Visual Recognition via Limited Latent Tokens
Human visual recognition is a sparse process, where only a few salient visual cues are attended to rather than traversing every detail uniformly. However, most current vision networks follow a dense paradigm, processing …
Image ClassificationSparse Representation-based ClassificationVideo ClassificationVita-CLIP: Video and text adaptive CLIP via Multimodal Prompting
Adopting contrastive image-text pretrained models like CLIP towards video classification has gained attention due to its cost-effectiveness and competitive performance. However, recent works in this area face a trade-off…
Action RecognitionPrompt LearningVideo ClassificationZero-Shot Action Recognition+1NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression
Video compression plays a significant role in IoT devices for the efficient transport of visual data while satisfying all underlying bandwidth constraints. Deep learning-based video compression methods are rapidly replac…
Deep LearningVideo ClassificationVideo CompressionSELF-VS: Self-supervised Encoding Learning For Video Summarization
Despite its wide range of applications, video summarization is still held back by the scarcity of extensive datasets, largely due to the labor-intensive and costly nature of frame-level annotations. As a result, existing…
Knowledge DistillationRepresentation LearningVideo ClassificationVideo SummarizationUnified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling
This paper simultaneously addresses three limitations associated with conventional skeleton-based action recognition; skeleton detection and tracking errors, poor variety of the targeted actions, as well as person-wise a…
Action LocalizationAction RecognitionActivity RecognitionData Augmentation+6Selective Structured State-Spaces for Long-Form Video Understanding
Effective modeling of complex spatiotemporal dependencies in long-form videos remains an open problem. The recently proposed Structured State-Space Sequence (S4) model with its linear complexity offers a promising direct…
Contrastive LearningFormToken ReductionVideo Classification+1The effectiveness of MAE pre-pretraining for billion-scale pretraining
This paper revisits the standard pretrain-then-finetune paradigm used in computer vision for visual recognition tasks. Typically, state-of-the-art foundation models are pretrained using large scale (weakly) supervised da…
Action ClassificationAction RecognitionFew-Shot Image Classificationimage-classification+6ViC-MAE: Self-Supervised Representation Learning from Images and Video with Contrastive Masked Autoencoders
We propose ViC-MAE, a model that combines both Masked AutoEncoders (MAE) and contrastive learning. ViC-MAE is trained using a global featured obtained by pooling the local representations learned under an MAE reconstruct…
Action ClassificationAction RecognitionContrastive Learningimage-classification+4Towards Activated Muscle Group Estimation in the Wild
In this paper, we tackle the new task of video-based Activated Muscle Group Estimation (AMGE) aiming at identifying active muscle regions during physical activity in the wild. To this intent, we provide the MuscleMap dat…
Activity RecognitionHuman Activity RecognitionKnowledge DistillationVideo ClassificationTemporal Coherent Test-Time Optimization for Robust Video Classification
Deep neural networks are likely to fail when the test data is corrupted in real-world deployment (e.g., blur, weather, etc.). Test-time optimization is an effective way that adapts models to generalize to corrupted data …
ClassificationSelf-Supervised LearningVideo ClassificationVideo4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks
To address the problem of medical image recognition, computer vision techniques like convolutional neural networks (CNN) are frequently used. Recently, 3D CNN-based models dominate the field of magnetic resonance image (…
ClassificationData AugmentationMRI classificationVideo Classification+2Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms
Real-time video surveillance, through CCTV camera systems has become essential for ensuring public safety which is a priority today. Although CCTV cameras help a lot in increasing security, these systems require constant…
Action RecognitionClassificationDeep Learningimage-classification+4Reversible Vision Transformers
We present Reversible Vision Transformers, a memory efficient architecture design for visual recognition. By decoupling the GPU memory requirement from the depth of the model, Reversible Vision Transformers enable scalin…
GPUimage-classificationImage Classificationobject-detection+2Augmenting Ego-Vehicle for Traffic Near-Miss and Accident Classification Dataset using Manipulating Conditional Style Translation
To develop the advanced self-driving systems, many researchers are focusing to alert all possible traffic risk cases from closed-circuit television (CCTV) and dashboard-mounted cameras. Most of these methods focused on i…
Image-to-Image TranslationTranslationUnsupervised Image-To-Image TranslationVideo ClassificationClass Prototypes Based Contrastive Learning for Classifying Multi-Label and Fine-Grained Educational Videos
The recent growth in the consumption of online media by children during early childhood necessitates data-driven tools enabling educators to filter out appropriate educational content for young learners. This paper p…
Contrastive LearningMathVideo ClassificationFew-Shot Video Classification via Representation Fusion and Promotion Learning
Recent few-shot video classification (FSVC) works achieve promising performance by capturing similarity across support and query samples with different temporal alignment strategies or learning discriminative feature…
Video Classification