Coauthors research on directing visual generation with an existing image or video. His papers separate the desired appearance from the structure and continuity that an edit should preserve.
Why read Patrick Esser?
Read Esser's coauthored video-synthesis paper to break a creative brief into appearance, structure and consistency across frames. The examples show why changing each frame independently can produce unstable video, and how preserving depth information also restricts possible shape changes. The method sections assume some knowledge of diffusion models.
The collaborative FLUX.1 Kontext report extends that question to image edits: how do an existing picture and a new instruction guide the next result? Read its iterative examples alongside the limitations section to see where identity and image quality can drift. Esser's current public profile links Black Forest Labs; these papers remain team contributions.
Start with the original
Selected work
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Coauthored research paper ·
Structure and Content-Guided Video Synthesis with Diffusion Models
What should change in a video, and what should stay? This coauthored paper separates content, scene structure and temporal consistency. Figures 1 and 4 introduce the controls; section 3.3 explains the structure tradeoff.
Cite this selection
XFollowList, “Structure and Content-Guided Video Synthesis with Diffusion Models” reading notes in the Patrick Esser profile. https://xfollowlist.com/people/patrick-esser#work-5620331af029
The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .
Profile-source checking date and references · Dated reading map
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Coauthored research paper ·
FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space
How does an existing image guide successive edits? Esser is among the report's authors. Read the edit examples and section 5 together: repeated edits can accumulate artifacts and lose detail.
Cite this selection
XFollowList, “FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space” reading notes in the Patrick Esser profile. https://xfollowlist.com/people/patrick-esser#work-c49a3001b131
The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .
Profile-source checking date and references · Dated reading map
Projects & roles
Gen-1 research
The project associated with Esser and collaborators' 2023 structure- and content-guided video paper.
FLUX.1 Kontext
Black Forest Labs' collaborative image-generation and editing research report, with Esser among its authors.
Community rating
Sources & further reading
Profile sources checked . This describes checking these references, separately from the publication dates of selected works.
- His named GitHub profile links @pess_r and the CompVis research repositories.
- Current public profile metadata identifies Patrick Esser, links his GitHub and associates his visual-generation work with @bfl_ml.
- The original author record names Esser, Chiu, Atighehchian, Granskog and Germanidis and gives the first submission date.
- The current collaborative report includes Esser and Rombach among the authors.
Cite this profile’s source check
XFollowList, Patrick Esser profile sources. Sources checked 2026-10-11. https://xfollowlist.com/people/patrick-esser#sources-checked