Article

Adaptive-Guided Latent Diffusion for Video Counterfactual Explanations with Multi-Scale Perceptual Refinement

2026-02-03

Abstract excerpt

The increasing reliance on deep learning models in video understanding necessitates transparent and interpretable decision-making, with video counterfactual explanations (CEs) offering a critical avenue to understand model behavior. However, generating effective video CEs remains challenging due to video data's high dimensionality, temporal coherence demands, and the need to balance precise alterations with visual...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 1b74cebe-ed0d-51f9-a59f-b3d8ccbfef11
DOI: 10.20944/preprints202602.0181.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Adaptive-Guided Latent Diffusion for Video Counterfactual Explanations with Multi-Scale Perceptual RefinementDOI 10.20944/preprints202602.0181.v1Read

Continuous Video Process: Modeling Videos as Continuous Multi-Dimensional Processes for Video PredictionSemantic proximity Read

MiniCausal-T2V: Towards Ultra-Low Latency and Memory-Efficient Causal Video Generation on Edge DevicesSemantic proximity Read

A Survey on Video Generation Technologies, Applications, and Ethical ConsiderationsSemantic proximity Read

VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations for Synthetic VideosSemantic proximity Read

Generative AI for Text-to-Video Generation: Recent Advances and Future DirectionsSemantic proximity Read

RobustVLM: Enhancing Large Vision-Language Models through Adaptive Visual Context Learning, Weak-to-Strong Robust Transfer, and Domain-Adaptive FeedbackSemantic proximity Read

Towards Human-Centered and Efficient Video Synthesis: A Survey of Multimodal Diffusion ModelsSemantic proximity Read

Tarsier2: Advancing Large Vision-Language Models from Detailed Video Descriptions to Comprehensive Video UnderstandingSemantic proximity Read

MotionCharacter: Identity-Preserving and Motion Controllable Human Video GenerationSemantic proximity Read

Navigating the Alignment Challenges of Diffusion Models: Insights and InnovationsSemantic proximity Read

Introduction to Diffusion Models, Autoencoders and Transformers: Review of Current AdvancementsSemantic proximity Read

LinGen-Uni: A Universal Linear-Complexity Framework for High-Resolution Minute-Length Text-to-Video GenerationSemantic proximity Read