Video Captioning
13개 벤치마크 · 논문 547편 · 이 태스크의 논문 보기 →
Benchmarks
MSR-VTT
MSVD
YouCook2
VATEX
ActivityNet Captions
MSRVTT-CTN
MSVD-CTN
Hindi MSR-VTT
Shot2Story20K
TVC
ChinaOpen-1k
MSVD-Indonesian
VidChapters-7M
Most implemented
ECO: Efficient Convolutional Network for Online Video Understanding
Top-down Visual Saliency Guided by Captions
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
RefCaptioner: Multi-Reference Image-Grounded Video Captioning
Papers
Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering
Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated text against ground-truth references. This paradigm suffers from th…
Question AnsweringVideo CaptioningCan We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators
Video-language models and video agents can produce hallucinations that conflict with spatiotemporal evidence. Existing benchmarks mainly evaluate model hallucinations, and heterogeneous mechanisms make detector reliabili…
Video Question AnsweringVideo CaptioningTAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding
Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To address this challenge, we propose TAU-Agent, an agentic retrieval-augmen…
Answer GenerationVideo CaptioningPL-NBA: A Possession-level Universal Basketball Video Dataset Supporting Multiple Visual Understanding Tasks
Visual understanding in sports has emerged as a hot topic in computer vision in recent years. Most existing basketball video datasets adopt single action or activity as sample, which can neither preserve the temporal con…
Temporal Action LocalizationAction AnticipationVideo CaptioningSterilizable Scene Graph Generation for Operating Rooms
Scene graph generation from surgical video enables a holistic and structured understanding of surgical scenes by modeling objects and their semantic relationships. Despite recent advances, state-of-the-art approaches rel…
Scene Graph GenerationScene UnderstandingObject DetectionVideo CaptioningAdaptive Two-Stage Visual Token Pruning for Efficient Inference in Video-Language Models
Vision-language models excel at image and video understanding but suffer from high inference latency due to the need to process thousands of tokens per image, limiting their deployment on resource-constrained edge device…
Video Captioning