Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
TikGuard: A Deep Learning Transformer-Based Solution for Detecting Unsuitable TikTok Content for Kids
The rise of short-form videos on platforms like TikTok has brought new challenges in safeguarding young viewers from inappropriate content. Traditional moderation methods often fall short in handling the vast and rapidly…
Video ClassificationBenchmarking Edge AI Platforms for High-Performance ML Inference
Edge computing's growing prominence, due to its ability to reduce communication latency and enable real-time processing, is promoting the rise of high-performance, heterogeneous System-on-Chip solutions. While current ap…
BenchmarkingCPUGPUVideo ClassificationPushing the boundaries of event subsampling in event-based video classification using CNNs
Event cameras offer low-power visual sensing capabilities ideal for edge-device applications. However, their high event rate, driven by high temporal details, can be restrictive in terms of bandwidth and computational re…
Event data classificationSensitivityVideo ClassificationScalable Frame Sampling for Video Classification: A Semi-Optimal Policy Approach with Reduced Search Space
Given a video with $T$ frames, frame sampling is a task to select $N \ll T$ frames, so as to maximize the performance of a fixed video classifier. Not just brute-force search, but most existing methods suffer from its va…
Video ClassificationInference-Scale Complexity in ANN-SNN Conversion for High-Performance and Low-Power Applications
Spiking Neural Networks (SNNs) have emerged as a promising substitute for Artificial Neural Networks (ANNs) due to their advantages of fast inference and low power consumption. However, the lack of efficient training alg…
image-classificationImage Classificationobject-detectionObject Detection+2ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition
Spiking Neural Networks (SNNs) have emerged as a compelling, energy-efficient alternative to traditional Artificial Neural Networks (ANNs) for static image tasks such as image classification and segmentation. However, in…
Action Recognitionimage-classificationImage ClassificationVideo ClassificationHERMES: temporal-coHERent long-forM understanding with Episodes and Semantics
Existing research often treats long-form videos as extended short videos, leading to several limitations: inadequate capture of long-range dependencies, inefficient processing of redundant information, and failure to ext…
FormVideo Classificationzero-shot long video breakpoint-mode question answeringzero-shot long video global-model question answering+2Attend-Fusion: Efficient Audio-Visual Fusion for Video Classification
Exploiting both audio and visual modalities for video classification is a challenging task, as the existing methods require large model architectures, leading to high computational complexity and resource requirements. S…
Video ClassificationVideo UnderstandingQuery-Efficient Video Adversarial Attack with Stylized Logo
Video classification systems based on Deep Neural Networks (DNNs) have demonstrated excellent performance in accurately verifying video content. However, recent studies have shown that DNNs are highly vulnerable to adver…
Adversarial AttackReinforcement Learning (RL)Style TransferVideo ClassificationVidModEx: Interpretable and Efficient Black Box Model Extraction for High-Dimensional Spaces
In the domain of black-box model extraction, conventional methods reliant on soft labels or surrogate datasets struggle with scaling to high-dimensional input spaces and managing the complexity of an extensive array of i…
image-classificationImage ClassificationModel extractionSynthetic Data Generation+1Learning Video Context as Interleaved Multimodal Sequences
Narrative videos, such as movies, pose significant challenges in video understanding due to their rich contexts (characters, dialogues, storylines) and diverse demands (identify who, relationship, and reason). In this pa…
Language ModelingLanguage ModellingQuestion AnsweringText Retrieval+5MultiHateClip: A Multilingual Benchmark Dataset for Hateful Video Detection on YouTube and Bilibili
Hate speech is a pressing issue in modern society, with significant effects both online and offline. Recent research in hate speech detection has primarily centered on text-based media, largely overlooking multimodal con…
Hate Speech DetectionVideo ClassificationUniForensics: Face Forgery Detection via General Facial Representation
Previous deepfake detection methods mostly depend on low-level textural features vulnerable to perturbations and fall short of detecting unseen forgery methods. In contrast, high-level semantic features are less suscepti…
Contrastive LearningDeepFake DetectionFace SwappingVideo ClassificationLookupViT: Compressing visual information to a limited number of tokens
Vision Transformers (ViT) have emerged as the de-facto choice for numerous industry grade vision solutions. But their inference cost can be prohibitive for many settings, as they compute self-attention in each layer whic…
Image Captioningimage-classificationImage ClassificationVideo ClassificationLearning Natural Consistency Representation for Face Forgery Video Detection
Face Forgery videos have elicited critical social public concerns and various detectors have been proposed. However, fully-supervised detectors may lead to easily overfitting to specific forgery methods or videos, and ex…
Representation LearningVideo ClassificationOpen Vocabulary Multi-Label Video Classification
Pre-trained vision-language models (VLMs) have enabled significant progress in open vocabulary computer vision tasks such as image classification, object detection and image segmentation. Some recent works have focused o…
Action ClassificationClassificationimage-classificationImage Classification+6PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection
Deepfake techniques generate highly realistic data, making it challenging for humans to discern between actual and artificially generated images. Recent advancements in deep learning-based deepfake detection methods, par…
DeepFake DetectionFace Swappingimage-classificationImage Classification+1MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning
Recent advancements in Machine Unlearning (MU) have introduced solutions to selectively remove certain training samples, such as those with outdated or sensitive information, from trained models. Despite these advancemen…
Machine Unlearningparameter-efficient fine-tuningVideo ClassificationPrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification
Video processing is generally divided into two main categories: processing of the entire video, which typically yields optimal classification outcomes, and real-time processing, where the objective is to make a decision …
ClassificationVideo ClassificationDL-KDD: Dual-Light Knowledge Distillation for Action Recognition in the Dark
Human action recognition in dark videos is a challenging task for computer vision. Recent research focuses on applying dark enhancement methods to improve the visibility of the video. However, such video processing resul…
Action RecognitionKnowledge DistillationTemporal Action LocalizationVideo Classification