kuavi-predictive

name	kuavi-predictive
description	Predictive video understanding — anticipate actions, predict future content, verify coherence, classify activities

Predictive Video Analysis

Use V-JEPA 2-powered predictive tools for forward-looking video understanding.

Tools

kuavi_anticipate_action

Predict what happens next after a given timestamp.

• Uses V-JEPA 2 predictor when available, falls back to embedding similarity
• Returns predicted action, confidence, and supporting evidence

kuavi_anticipate_action(time_point=45.0)

kuavi_predict_future

Predict future video content from a time range.

• Temporal continuation using V-JEPA 2 predictor embeddings
• Returns predicted content description with confidence

kuavi_predict_future(start_time=30.0, end_time=45.0)

kuavi_verify_coherence

Score temporal coherence across video segments and detect anomalies.

• Compares predicted vs actual embeddings at segment boundaries
• Flags surprising transitions where prediction diverges from reality

kuavi_verify_coherence()

kuavi_classify_segment

Classify a video segment using attentive probes trained on benchmark tasks.

• Available tasks: SSv2, K400, Diving48, and more
• Returns top-K class labels with confidence scores

kuavi_classify_segment(start_time=10.0, end_time=20.0)

Example Workflows

"What happens next?"

1. kuavi_search_video("current activity", field="action") to locate the moment
2. kuavi_anticipate_action(time_point=<end_of_activity>) to predict next action
3. kuavi_extract_frames around the predicted time to verify

"Is this video coherent?"

1. kuavi_verify_coherence() to get per-segment coherence scores
2. Look for segments with low coherence (anomalies)
3. kuavi_extract_frames around anomalous transitions to inspect

"Classify this activity"

1. kuavi_classify_segment(start_time, end_time) for benchmark labels
2. Cross-reference with kuavi_search_video(field="action") for caption-based description