📢 #Gate Square Writing Contest Phase 3# is officially kicks off!
🎮 This round focuses on: Yooldo Games (ESPORTS)
✍️ Share your unique insights and join promotional interactions. To be eligible for any reward, you must also participate in Gate’s Phase 286 Launchpool, CandyDrop, or Alpha activities!
💡 Content creation + airdrop participation = double points. You could be the grand prize winner!
💰Total prize pool: 4,464 $ESPORTS
🏆 First Prize (1 winner): 964 tokens
🥈 Second Prize (5 winners): 400 tokens each
🥉 Third Prize (10 winners): 150 tokens each
🚀 How to participate:
1️⃣ Publish an
Plug and play, perfectly compatible: The SD community's image video plug-in I2V-Adapter is here
Bit Recently, a new research result led by Kuaishou, "I2V-Adapter: A General Image-to-Video Adapter for Video Diffusion Models", was released, which introduced an innovative image-to-video conversion method and proposed a lightweight adapter module, namely I2V-Adapter, which converts static images into dynamic videos without changing the original structure and pre-trained parameters of existing text-to-video generation (T2V) models.
Compared with existing methods, I2V-Adapter significantly reduces the trainable parameters (down to 22M, which is the mainstream solution such as Stable Video Diffusion [1][2] of 1%), which is also compatible with Stable Diffusion [3] Community-developed custom T2I model (DreamBooth [4]、Lora [5]) and control tools (ControlNet Compatibility. Through experiments, the researchers have demonstrated the effectiveness of the I2V-Adapter in generating high-quality video content, opening up new possibilities for creative applications in the field of I2V.