HouseTour: Automating Real Estate Videos with AI
The Problem
Making professional-quality real estate videos is a pain. You need a camera operator, editing skills, and tools to stitch everything together. Sure, you could fake it with a phone and bad transitions, but if you’re trying to sell a house (or impress a client), that’s not going to cut it. The kicker? AI tools exist for generating text or images, but they’re clueless when it comes to understanding 3D spaces. Smooth camera paths? Forget it.
What This Does
HouseTour handles two key tasks: creating smooth 3D camera trajectories and generating natural language descriptions of spaces—all from a bunch of images. The magic happens via a diffusion-based planner (config/residualdiffuser.py) that refines sparse input poses into buttery-smooth camera paths. Combine that with their Qwen2-VL-3D adapter (buried in diffuser/models/) that merges visual, spatial, and language info, and you’ve got a system that understands the space it’s describing.
The dataset (data/) is the backbone here: over 1,200 professional house-tour videos with camera poses, 3D reconstructions, and text descriptions. This isn’t some toy dataset—it’s built for training the model to handle real-world scenarios. The output? A 3D video of the space (rendered with 3D Gaussian splatting—yeah, that’s a thing) and a natural-language summary that sounds like a real estate agent who has their life together.
The file structure is clean enough, but there’s some cruft in pycache folders, which could’ve been .gitignored. The heavy lifting is all in diffuser/, particularly in models/ where the diffusion and helper logic lives.
Real-World Use
Say you’re a real estate agent with a folder of room images. Fire up this repo, run the pipeline (🏋️ Training & Inference section in the README), and boom: you’ve got a smooth video tour and a description like “This sunlit kitchen features a modern backsplash and stainless steel appliances.” You didn’t even break a sweat.
python diffuser/models/diffusion.py --input <imagefolder> --output <video_path>
It’s also a godsend for VR/AR setups or companies selling virtual tours. The heavy reliance on GPU resources (it’s tested on an NVIDIA A100 with CUDA 12.4) means you’ll need serious hardware.
The Bottom Line
HouseTour is a niche but impressive tool. If you’re in real estate, VR, or just want to play with AI-powered 3D rendering and text generation, this is worth a look. Downsides? It’s overkill for small projects, and the lack of user-friendly abstraction (it’s all very research-y) makes it a tough sell for non-technical users. But if you love tinkering and have the hardware, this is definitely a cool toy.