u/Clean-Ad-5663

So I've been messing around with this open-source model lately, and honestly, it's a pretty wild take on getting 3D stuff from pictures. Figured some folks here might find it interesting.

It's called SenseNova-Vision, and it's a 7B multimodal model. Apache 2.0 license, which is cool. Basically, it just sees computer vision as one big generation problem. You throw a bunch of images at it, give it some natural language instructions, and it spits out text, images, or both.

What's actually relevant for us photogrammetry nerds is that multi-view 3D reconstruction and camera pose estimation are built right in. No weird task-specific bits, no separate feature matching step. Just one model, one prompt. Pretty neat.

I tried a few things:

For multi-view reconstruction, I fed it some indoor and outdoor shots. It gives you these multi-view point maps. Honestly, the object and indoor results look pretty usable. Outdoor scenes are a bit rougher, edges get kinda soft.

Then there's camera pose estimation. It just gives you camera parameters directly from the images. I haven't actually benchmarked it against COLMAP yet, so no big claims on accuracy there. But the workflow is definitely not what I'm used to. No patch match, no CUDA dependency, no dense reconstruction pass. It's just... different.

Oh, and the same model also does segmentation, depth, keypoints, OCR. So it's one set of weights for a bunch of stuff, instead of needing a whole toolbox of specialized pipelines.

Now, for the real talk:

This is neural reconstruction, not the traditional SfM we're used to. If you absolutely need sub-millimeter accuracy, this probably isn't gonna replace COLMAP. Not right now, anyway.

It also needs some serious hardware. The web demo suggests 1x80GB GPU, and for a full benchmark, they're talking 8x80GB. Yikes.

Plus, the weights literally just dropped on July 8th, so there are definitely some rough edges to expect.

Here are the links if you wanna poke around:

HF demo: https://huggingface.co/spaces/sensenova/SenseNova-Vision

Weights: https://huggingface.co/sensenova/SenseNova-Vision-7B-MoTCode

GitHub: https://github.com/OpenSenseNova/SenseNova-Vision

Anyone else tried this or something similar? I'm curious what people think. I'd love to see someone compare neural reconstruction against COLMAP on the same image sets. That's the real test I need before I'd trust it for any serious work.

I absolutely love watching live sports; it's one of my few forms of entertainment. Initially, I just watched on a regular TV because of its larger size and better viewing experience. Of course, I didn't actively seek out other products; I just thought as long as I could watch, it was fine. However, the real turning point came when I visited a friend. He showed off his RayNeo Air 4 Pro, and after trying it out, I admit I was blown away by this high-tech product, haha. And that's how I got my first pair of AR glasses.

I think the biggest difference during the experience was the aspect ratio. It felt like having a great seat in a movie theater and watching live sports. While that's a bit abstract, I felt much more immersed, as if the game was happening right in front of me.

The HDR10 display also played a crucial role in fast-paced matches. Vibrant jerseys, stadium lights, and details in darker areas like shadows on the field and below the stands were much easier to discern. Compared to watching on a laptop, the picture felt more balanced and pleasing to the eye.

Dynamic visuals were another aspect I focused on. I initially thought the fast-paced games, quick passes, and player movement on the field would be difficult for AR glasses to handle, but the actual experience was much smoother than I expected. Being able to capture details of the game—such as the direction of passes or the progression of the match—made the viewing experience much more immersive.

However, there are a few things to keep in mind. The best viewing experience is achieved in a comfortable sitting position. If I move too much or lean forward, the image clarity decreases slightly. Strong indoor lighting can also affect the overall effect.

But what surprised me most was how easily I became immersed in the game. In one match, I was so focused that I completely forgot I was wearing glasses until I went to adjust them.

I still enjoy watching sports on a regular TV, especially with friends. But when I just want to calmly focus on the game, the immersion provided by the larger virtual screen is something I didn't expect.

Has anyone else tried watching live sports with AR glasses? I'm curious how it compares to your usual viewing methods.