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Found 6 papers, 1 papers with code
Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs
Long-form video understanding with Large Vision Language Models is challenged by the need to analyze temporally dispersed yet spatially concentrated key moments within limited context windows.
Human Action Anticipation: A Survey
Predicting future human behavior is an increasingly popular topic in computer vision, driven by the interest in applications such as autonomous vehicles, digital assistants and human-robot interactions.
BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation
We introduce the BEHAVIOR Vision Suite (BVS), a set of tools and assets to generate fully customized synthetic data for systematic evaluation of computer vision models, based on the newly developed embodied AI benchmark, BEHAVIOR-1K.
SF-Net: Single-Frame Supervision for Temporal Action Localization
To obtain the single-frame supervision, the annotators are asked to identify only a single frame within the temporal window of an action.
Ranked #5 on
Weakly Supervised Action Localization
on BEOID
Only Time Can Tell: Discovering Temporal Data for Temporal Modeling
However, in current video datasets it has been observed that action classes can often be recognized without any temporal information from a single frame of video.
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification
Our proposed late fusion of CNN- and motion-based features can further increase the mean average precision (mAP) on MED'14 from 34. 95% to 38. 74%.
