SOTAVerified

Video Understanding

A crucial task of Video Understanding is to recognise and localise (in space and time) different actions or events appearing in the video.

Source: Action Detection from a Robot-Car Perspective

Papers

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Showing 626–650 of 1149 papers

TitleStatusHype
Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer LearningCode1
GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation—0
Mug-STAN: Adapting Image-Language Pretrained Models for General Video UnderstandingCode1
PG-Video-LLaVA: Pixel Grounding Large Video-Language ModelsCode2
Vamos: Versatile Action Models for Video UnderstandingCode0
SPOT! Revisiting Video-Language Models for Event Understanding—0
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video UnderstandingCode2
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab—0
Beyond still images: Temporal features and input variance resilience—0
ZEETAD: Adapting Pretrained Vision-Language Model for Zero-Shot End-to-End Temporal Action Detection—0
MM-VID: Advancing Video Understanding with GPT-4V(ision)Code1
Videoprompter: an ensemble of foundational models for zero-shot video understanding—0
Query-aware Long Video Localization and Relation Discrimination for Deep Video Understanding—0
A Survey on Video Diffusion ModelsCode4
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks—0
DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model—0
Telling Stories for Common Sense Zero-Shot Action RecognitionCode0
A Content-Driven Micro-Video Recommendation Dataset at ScaleCode2
BT-Adapter: Video Conversation is Feasible Without Video Instruction TuningCode1
End-to-End Streaming Video Temporal Action Segmentation with Reinforce LearningCode1
M^33D: Learning 3D priors using Multi-Modal Masked Autoencoders for 2D image and video understanding—0
Towards Surveillance Video-and-Language Understanding: New Dataset, Baselines, and Challenges—0
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding—0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Language as the Medium: Multimodal Video Classification through text only—0
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