
Kaiju (from , ), or giant movie monster, are terms used in film and media for monsters, and the like, of enormous size, mainly belonging to a designated genre, known as kaiju movies, or giant monster movies, where they are usually depicted attacking major cities, and battling either the military or other creatures, mixing creature features with the disaster film genre, but also often involving science fiction. Examples include famous movie monsters like King Kong, Godzilla and Gamera, cult classics like The Beast from 20,000 Fathoms, It Came from Beneath the Sea, Them!
Kaiju (from , ), or giant movie monster, are terms used in film and media for monsters, and the like, of enormous size, mainly belonging to a designated genre, known as kaiju movies, or giant monster movies, where they are usually depicted attacking major cities, and battling either the military or other creatures, mixing creature features with the disaster film genre, but also often involving science fiction. Examples include famous movie monsters like King Kong, Godzilla and Gamera, cult classics like The Beast from 20,000 Fathoms, It Came from Beneath the Sea, Them!, The Giant Claw, and modern examples like Cloverfield, among others. Related media also includes various "mecha", which often revolve around giant robots fighting giant monsters, such as Voltron, Power Rangers, Evangelion, Megas XLR, Pacific Rim, etc.
Historically, giant movie monsters were known in Japanese as daikaijū ( ), however the broader term of "kaiju" has largely replaced this. The term can refer to the monsters themselves or the movie genre in which they appear. In contrast to "giant movie monster", the term "kaiju" is generally used to specifically refer to the Japanese style of giant monster media, which traditionally uses actors in monster suits and scale model sets. Its widespread contemporary use is credited to tokusatsu (special effects) director Eiji Tsuburaya and filmmaker Ishirō Honda, who popularized the Japanese kaiju film genre by creating the Godzilla franchise and its spin-offs.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).