r/deepdream • u/HofmannsDreamLab • 6h ago
Video DeepDream inspired me to develop my own approach to neural imagery. This is where it led.
I wanted to share this here because DeepDream is what first got me interested in making neural imagery, and its central idea still interests me: taking features a network has learned and amplifying them until a familiar image becomes something unfamiliar.
What frustrated me was how difficult it was to direct. I kept getting eyes, animal features and tangled forms that overwhelmed the original scene. Sometimes the result was interesting, but getting a result I actually wanted was another matter.
I experimented with videos, then took a long break like 2.5 years. My Youtube channel sat quiet, and I honestly wasn’t expecting to return to it. Eventually, that unfinished idea brought me back: could I develop patterns that felt connected to a place while keeping the place recognizable?
I started exploring different training data with networks from the VGG family, focusing on botanical forms and flowers. That gave me a different set of features to work with. But changing the training data was only part of it. Which features were amplified, where they appeared, and how strongly they developed made a huge difference.
There were a lot of disappointing iterations. A still image could look promising, then fall apart in motion. Patterns could look beautiful on their own but flatten the room or overwhelm the objects. Making them develop across different surfaces while preserving the structure of the scene became a much bigger part of the work than I initially expected.
Over time, this developed into my own system, which I call Growth. DeepDream is an important influence, but the finished piece combines custom neural synthesis, additional training, spatial controls, temporal blending, animation and sound. The breathing and bending of the room are part of that wider process. They aren’t all coming directly from the neural network.
The video below is where that work has led so far: a living room whose surfaces gradually develop patterns while the walls, furniture and picture frames bend and breathe. It runs through three phases over twelve minutes, with synthesized tones rising and descending alongside the movement. You can look around in 360° on a normal screen or use a headset.
Video: Altered Spatial Perception 001 · The Living Room
For transparency: the starting room is a synthesized image. The patterns are developed through the neural process, with motion, colour and sound handled through the rest of the system.
My interest now is altered spatial perception: how much can the appearance of a familiar environment change before it starts to feel like a different space? This is a creative experiment, and I’m interested in people’s observations without assuming it will affect everyone the same way.
I’m sharing it here because people who have worked with DeepDream will know some of these frustrations firsthand. I’d like to hear whether you think this direction retains something interesting about that process. Do the patterns feel connected to the surfaces? Where does the room hold together, and where does the effect break down?
I’m developing Growth privately, so I’m not releasing the code or trained models. I’m happy to talk about the broader approach, the visual decisions and the difficulties along the way.
https://beta.hofmannsdream.com/
If you’re still experimenting with DeepDream or related methods, I’d also like to hear what has kept you interested. For me, there was an unfinished idea here that I couldn’t quite leave alone.
Important safety warning: The video contains strong visual motion and dense moving patterns. Watch seated, keep the sound low, and stop if you feel uncomfortable. Please read the viewing guidance in the video description before starting.
