Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models · HackerPapers discussions

Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models — mentioned by yeldarb

Wed, 24 Jun 2026 17:35:13 GMT

> See the url in my comment (search for the term rfdetr-2xlarge). 2XL does indeed go up to 800x800 and has PML1.0 license instead of apache 2.0. All of the models, including the Apache 2.0 ones, can be configured to go higher than 800x800. The difference between the ones with the PML license and the Apache 2.0 ones is the backbone, not the resolution. I'd suggest you read the ICLR paper[1] which shows clearly the difference between the backbones at various latencies in Figure 1. > For many domain-specific (often less common and odd dimensioned) objects, downscaling will severely reduce…

Paper and discussion history. A mention is not an endorsement.

Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models — mentioned by smus

Thu, 10 Jul 2025 15:05:01 GMT

We benchmarked Gemini 2.5 on 100 open source object detection datasets in our paper: https://arxiv.org/abs/2505.20612 (see table 2) Notably, performance on out of distribution data like those in RF100VL is super degraded It worked really well zero-shot (comparatively to the foundation model field) achieving 13.3 average mAP, but counterintuitively performance degraded when provided visual examples to ground its detections from, and when provided textual instructions on how to find objects as additional context. So it seems it has some amount of object detection zero-shot training, probably on…

Paper and discussion history. A mention is not an endorsement.