Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Time- Memory- and Parameter-Efficient Visual Adaptation
As foundation models become more popular there is a growing need to efficiently finetune them for downstream tasks. Although numerous adaptation methods have been proposed they are designed to be efficient only in te…
GPUVideo ClassificationRevisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach
Weakly-supervised temporal action localization aims to localize action instances in videos with only video-level action labels. Existing methods mainly embrace a localization-by-classification pipeline that optimizes the…
Action LocalizationClassificationClusteringTemporal Action Localization+3InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
The exponential growth of large language models (LLMs) has opened up numerous possibilities for multimodal AGI systems. However, the progress in vision and vision-language foundation models, which are also critical eleme…
Image RetrievalImage-to-Text RetrievalLanguage ModellingLarge Language Model+11A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
Video segmentation requires consistently segmenting and tracking objects over time. Due to the quadratic dependency on input size, directly applying self-attention to video segmentation with high-resolution input feature…
GPUObjectObject TrackingPanoptic Segmentation+5Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments
Deep learning-based models are at the forefront of most driver observation benchmarks due to their remarkable accuracies but are also associated with high computational costs. This is challenging, as resources are often …
Activity RecognitionAutonomous DrivingComputational EfficiencyKnowledge Distillation+2Neural architecture impact on identifying temporally extended Reinforcement Learning tasks
Inspired by recent developments in attention models for image classification and natural language processing, we present various Attention based architectures in reinforcement learning (RL) domain, capable of performing …
Deep Reinforcement Learningimage-classificationImage ClassificationOpenAI Gym+4Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding
While most modern video understanding models operate on short-range clips, real-world videos are often several minutes long with semantically consistent segments of variable length. A common approach to process long vide…
Action LocalizationFormTemporal Action LocalizationVideo Classification+1Language as the Medium: Multimodal Video Classification through text only
Despite an exciting new wave of multimodal machine learning models, current approaches still struggle to interpret the complex contextual relationships between the different modalities present in videos. Going beyond exi…
Action RecognitionVideo ClassificationVideo UnderstandingDifferentiable Resolution Compression and Alignment for Efficient Video Classification and Retrieval
Optimizing video inference efficiency has become increasingly important with the growing demand for video analysis in various fields. Some existing methods achieve high efficiency by explicit discard of spatial or tempor…
RetrievalVideo ClassificationVideo RetrievalAV-MaskEnhancer: Enhancing Video Representations through Audio-Visual Masked Autoencoder
Learning high-quality video representation has shown significant applications in computer vision and remains challenging. Previous work based on mask autoencoders such as ImageMAE and VideoMAE has proven the effectivenes…
Video ClassificationText-to-feature diffusion for audio-visual few-shot learning
Training deep learning models for video classification from audio-visual data commonly requires immense amounts of labeled training data collected via a costly process. A challenging and underexplored, yet much cheaper, …
ClassificationFew-Shot LearningVideo ClassificationIdentifying Misinformation on YouTube through Transcript Contextual Analysis with Transformer Models
Misinformation on YouTube is a significant concern, necessitating robust detection strategies. In this paper, we introduce a novel methodology for video classification, focusing on the veracity of the content. We convert…
ArticlesClassificationFew-Shot LearningMisinformation+6MUVF-YOLOX: A Multi-modal Ultrasound Video Fusion Network for Renal Tumor Diagnosis
Early diagnosis of renal cancer can greatly improve the survival rate of patients. Contrast-enhanced ultrasound (CEUS) is a cost-effective and non-invasive imaging technique and has become more and more frequently used f…
Video ClassificationPatch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
The ubiquitous and demonstrably suboptimal choice of resizing images to a fixed resolution before processing them with computer vision models has not yet been successfully challenged. However, models such as the Vision T…
FairnessImage ClassificationNavigateobject-detection+3The Staged Knowledge Distillation in Video Classification: Harmonizing Student Progress by a Complementary Weakly Supervised Framework
In the context of label-efficient learning on video data, the distillation method and the structural design of the teacher-student architecture have a significant impact on knowledge distillation. However, the relationsh…
Knowledge DistillationPseudo LabelVideo ClassificationWeakly-supervised LearningActive Learning for Video Classification with Frame Level Queries
Deep learning algorithms have pushed the boundaries of computer vision research and have depicted commendable performance in a variety of applications. However, training a robust deep neural network necessitates a large …
Active LearningClassificationVideo ClassificationLearning Unseen Modality Interaction
Multimodal learning assumes all modality combinations of interest are available during training to learn cross-modal correspondences. In this paper, we challenge this modality-complete assumption for multimodal learning …
RetrievalVideo ClassificationBoosting Breast Ultrasound Video Classification by the Guidance of Keyframe Feature Centers
Breast ultrasound videos contain richer information than ultrasound images, therefore it is more meaningful to develop video models for this diagnosis task. However, the collection of ultrasound video datasets is much ha…
Video ClassificationInflated 3D Convolution-Transformer for Weakly-supervised Carotid Stenosis Grading with Ultrasound Videos
Localization of the narrowest position of the vessel and corresponding vessel and remnant vessel delineation in carotid ultrasound (US) are essential for carotid stenosis grading (CSG) in clinical practice. However, the …
Video ClassificationMulti-label Video Classification for Underwater Ship Inspection
Today ship hull inspection including the examination of the external coating, detection of defects, and other types of external degradation such as corrosion and marine growth is conducted underwater by means of Remotely…
ClassificationVideo Classification