FrameThrower · Actors · Ezra Miller
Ezra Miller
8 films · 769 frames · top-billed in 4 · 2008–2023
Born 30 September 1992 · Wyckoff, New Jersey, USA
Ezra Matthew Miller is an American actor. Their feature film debut was in Afterschool (2008), which they followed by starring in the dramas We Need to Talk About Kevin (2011) and The Perks of Being a Wallflower (2012).
After a supporting role in the comedy Trainwreck (2015), Miller played Credence Barebone in the Fantastic Beasts fantasy films Fantastic Beasts and Where to Find Them (2016), Fantastic Beasts: The Crimes of Grindelwald (2018), and Fantastic Beasts: The Secrets of Dumbledore (2022). In 2020, they had a recurring role on the miniseries The Stand. Miller played the Flash in the DC Extended Universe, including in the films Justice League (2017) and The Flash (2023).
Awards
On FrameThrower we have: 8 films · 769 frames · top-billed in 4 · 2008–2023
- Trophée Chopard
How their films are shot
Measured across 769 frames from the 8 films we hold. This is the look of the work Ezra takes, not a claim about any single frame — we index the cast of a film, never the people in a shot.
Across the 8 films we hold, 52% of their frames are night, 53% low key — the look of the work Ezra takes.
Time of day
Lighting
Shot size
Camera angle
Mood
Films in the library
Every poster opens that film — stills, cinematography notes and colour palette.
The Flash
2023 · Barry Allen / The Flash
The Perks of Being A Wallflower
2012 · Patrick
We Need To Talk About Kevin
2011 · Kevin Khatchadourian, Teenager
Afterschool
2008 · Robert
Zack Snyder's Justice League
2021 · The Flash / Barry Allen
Fantastic Beasts: The Crimes of Grindelwald
2018 · Credence Barebone
Justice League
2017 · The Flash / Barry Allen
Fantastic Beasts and Where to Find Them
2016 · Credence Barebone
Often with
Shared films in this library, not a full filmography.
A reference database for filmmakers
FrameThrower is a fully machine-searchable film database and visual reference library — all 769 frames from Ezra Miller's 8 films, and 5,000+ films besides, indexed frame by frame and readable by AI. Search it in plain language, from a reference image, or by colour; call it from an API, an MCP server or an SDK. It's the reference layer for making the next movie.