Tokyo Rain Chase — Context-IR Side-by-Side
The same 15-second rainy-night car chase prompt, compared side by side: the original 2K output versus the Context-IR-rewritten, super-resolved version. 20 shot changes plus a slow-motion water splash — a real-world test sample for a prompt-rewriting tool.
PROMPT · Original Video Prompt
Create with AI这段15秒飙车视频的原始提示词如下：
这是一部好莱坞动作片电影片断，是都市汽车飙车的电影，时间是雨后，晚上，地点在东京街头，两辆车在街头追逐，最后，在东京桥上，后面的橙色跑车把前面那辆黑色的奔驰撞下桥，黑色车落水，橙色车成功开远，15秒时间要有20个景别镜头切换，落水时要有慢动作
用了Context-IR后，生成了一段新的提示词，我放在评论区。原始提示词我直接生成了2K，用Context-IR这段视频我先生成768P后进行官方版的超分，两段视频我进行了同轴对比，你认为哪个更好？0:08 / 0:
這段15秒飆車影片的原始提示詞如下：
這是一部好萊塢動作片的電影片段，是都市汽車飆車的電影，時間點是雨後的夜晚，地點在東京街頭，兩輛車在街頭互相追逐，最後在東京的一座橋上，後方的橘色跑車把前面那輛黑色賓士撞下橋，黑色車墜入水中，橘色車則順利揚長而去，15秒內要有20個景別的鏡頭切換，車子落水的瞬間要用慢動作呈現。
用了Context-IR之後，生成了一段新的提示詞，我放在留言區了。原始提示詞我直接生成2K，用Context-IR這段影片我先生成768P後，再做官方版的超解析度放大，兩段影片我做了同軸比較，你覺得哪一個比較好？0:08 / 0:
The original prompt for this 15-second car chase video is as follows:
This is a Hollywood action movie clip, an urban car chase film. The time is after rain, at night, and the location is the streets of Tokyo. Two cars chase each other through the streets, and finally, on a bridge in Tokyo, the orange sports car behind rams the black Mercedes in front off the bridge. The black car falls into the water, and the orange car successfully speeds away. Within the 15 seconds there should be 20 shot/angle cuts, and slow motion should be used when the car falls into the water.
After using Context-IR, a new prompt was generated, which I've posted in the comments. For the original prompt I generated 2K directly; for the Context-IR version I first generated it at 768P and then did official super-resolution upscaling. I did a side-by-side comparison of the two videos — which one do you think is better? 0:08 / 0:
この15秒間のカーチェイス動画の元のプロンプトは以下の通りです:
これはハリウッドのアクション映画の一場面で、都市部でのカーチェイスを描いた映画です。時間は雨上がりの夜、場所は東京の街頭。二台の車が街頭で追いかけ合い、最後には東京の橋の上で、後ろにいるオレンジ色のスポーツカーが前を走る黒いベンツを橋から突き落とし、黒い車は水中に落下し、オレンジ色の車はうまく走り去っていく。15秒の中に20のカット・アングル切り替えが必要で、水に落ちる瞬間はスローモーションにすること。
Context-IRを使った後、新しいプロンプトが生成されたので、コメント欄に載せておきます。元のプロンプトは直接2Kで生成し、Context-IRを使ったこの動画はまず768Pで生成した後、公式版の超解像処理を行いました。二つの動画を同じ軸で比較してみたのですが、どちらの方が良いと思いますか? 0:08 / 0:
이 15초짜리 카체이스 영상의 원본 프롬프트는 다음과 같다:
이것은 할리우드 액션 영화의 한 장면으로, 도심 자동차 추격전을 다룬 영화다. 시간은 비 온 뒤 밤이고, 장소는 도쿄 시내 거리다. 두 대의 차가 거리에서 서로 추격하다가, 마지막에 도쿄의 한 다리 위에서 뒤따르던 주황색 스포츠카가 앞서가던 검은색 벤츠를 다리 아래로 밀어 떨어뜨린다. 검은 차는 물에 빠지고, 주황색 차는 성공적으로 멀리 달아난다. 15초 동안 20번의 숏/앵글 전환이 있어야 하며, 차가 물에 떨어질 때는 슬로모션을 사용해야 한다.
Context-IR을 사용한 뒤 새로운 프롬프트가 생성되었는데, 댓글란에 올려두었다. 원본 프롬프트는 바로 2K로 생성했고, Context-IR 버전은 먼저 768P로 생성한 뒤 공식 버전의 업스케일링(초해상도)을 진행했다. 두 영상을 나란히 비교해봤는데, 어느 쪽이 더 낫다고 생각하는가? 0:08 / 0:
✍️ Editor’s Notes
This isn't really a standard video prompt — it's a discussion post comparing a raw prompt against Context-IR processing, so on its own the content is pretty thin. It's basically one summary line: Tokyo, rainy night, car chase, crash into the river, twenty shot-angle cuts. The actual keyword density and structural detail got dumped into the comments, so read in isolation this thing is incomplete. Running the comparison on MiniMax H3 tracks too, since that class of model is sensitive to prompt refinement — what the author's actually testing is whether a hand-polished short prompt can beat the tool-preprocess-then-upscale pipeline. This is a workflow experiment log, not a pure creative prompt.
Want tighter control? Try this expanded version:
A 15-second urban night car chase with Hollywood action-movie texture. Post-rain Tokyo streets, pavement reflecting like a mirror, neon lights shattering into scattered points of light across the standing water. A black Mercedes leads, an orange sports car chases behind; tires kick up water mist mid-pursuit at high speed. Twenty different shot angles cut rapidly — low-angle ground-level tracking, reverse shots from inside the car, and overhead aerial views all take their turn, edited tight with no dead air. The climax lands on a Tokyo river-crossing bridge: the orange sports car side-rams the black Mercedes and forces it through the guardrail into the river below. Cut to slow motion here — water spray, the car tumbling, glass shattering, all visible frame by frame, with the sound briefly dropping out to create a suspended, weightless feeling. The orange sports car doesn't linger — it accelerates off the bridge, its taillights disappearing into the rainy night street, and the footage returns to normal speed to close out.
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