Key reading
1. FlowEdit (ICCV 2025)
- Link: FlowEdit (ICCV 2025)
- Role: Inference-time transport
- Why important: Editing follows a difference between target and source velocity fields.
- Main limitation: The original work addresses images; a video adaptation changes the backbone and must verify temporal behavior.
- Discussion question: How does source preservation interact with changes in motion?
2. DynaEdit
- Link: DynaEdit
- Role: Dynamic rewriting
- Why important: Its source-query and guidance design motivates a separate discussion of preserving appearance while changing dynamics.
- Main limitation: Sampling controls do not by themselves establish correct object contact or event replacement.
- Discussion question: Which failures come from the control signal, and which come from the backbone?
3. Bernini
- Link: Bernini
- Role: Semantic planning and rendering
- Why important: A semantic planner and a renderer expose different roles for edit intent and visual detail.
- Main limitation: The deck follows the existing v1 method audit; it does not claim a completed v2 difference audit.
- Discussion question: Which planner supervision improves action semantics without unwanted source changes?
4. World in World
- Link: World in World
- Role: Source-grounded world-model editing
- Why important: Source observations and correspondence-based evidence support controlled re-observation and editing.
- Main limitation: Camera-rendering evidence should not be treated as proof of arbitrary physical interaction editing.
- Discussion question: How should hidden state and contact uncertainty enter the editing interface?
5. MMLVE-Agent
- Link: MMLVE-Agent
- Role: Editing agents
- Why important: Shot assignment, global visual references, and feedback separate orchestration from pixel generation.
- Main limitation: External editor capability, service failures, and retry costs influence the end-to-end result.
- Discussion question: Does planning improve success over a fixed workflow at the same call budget?
6. CoVEBench
- Link: CoVEBench
- Role: Compositional evaluation
- Why important: Fine-grained checks help separate individual instruction requirements.
- Main limitation: A compositional instruction is different from a sequence of requests with history and selective undo.
- Discussion question: Which event and session annotations reveal failures hidden by aggregate quality?
Paper and model index
Example and asset notes