SOTAVerified

Video Classification

Video Classification is the task of producing a label that is relevant to the video given its frames. A good video level classifier is one that not only provides accurate frame labels, but also best describes the entire video given the features and the annotations of the various frames in the video. For example, a video might contain a tree in some frame, but the label that is central to the video might be something else (e.g., “hiking”). The granularity of the labels that are needed to describe the frames and the video depends on the task. Typical tasks include assigning one or more global labels to the video, and assigning one or more labels for each frame inside the video.

Source: Efficient Large Scale Video Classification

Papers

Showing 110 of 455 papers

TitleStatusHype
ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence AlignmentCode0
Exploring Audio Cues for Enhanced Test-Time Video Model AdaptationCode0
Spatiotemporal Analysis of Forest Machine Operations Using 3D Video Classification0
Video-GPT via Next Clip DiffusionCode1
Read My Ears! Horse Ear Movement Detection for Equine Affective State AssessmentCode0
Perception Encoder: The best visual embeddings are not at the output of the networkCode8
TenAd: A Tensor-based Low-rank Black Box Adversarial Attack for Video Classification0
Unbiasing through Textual Descriptions: Mitigating Representation Bias in Video Benchmarks0
Spatiotemporal Learning with Context-aware Video Tubelets for Ultrasound Video Analysis0
Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MultigridmAP38.2Unverified