Proof pending. This topic has not reached the minimum paper threshold yet.
Video object removal aims to eliminate target objects from videos while plausibly completing missing regions and preserving spatio-temporal consistency. Although diffusion models have recently advance...
Existing video object removal methods excel at inpainting content "behind" the object and correcting appearance-level artifacts such as shadows and reflections. However, when the removed object has mo...
We study object motion path editing in videos, where the goal is to alter a target object's trajectory while preserving the original scene content. Unlike prior video editing methods that primarily ma...
Maintaining background consistency while enhancing foreground quality remains a core challenge in video editing. Injecting full-image information often leads to background artifacts, whereas rigid bac...
Freshness
Canonical route: /topics
Agent Handoff
Canonical ID video-editing | Route /topic/video-editing
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/video-editingMCP example
{
"tool": "search_papers",
"arguments": {
"query": "Video Editing",
"cluster": "Video Editing"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "Video Editing",
"normalized_query": "video-editing",
"route": "/topic/video-editing",
"paper_ref": null,
"topic_slug": "video-editing",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.