segmentation

Google DeepMind researchers developed GenCeption, which repurposes Alibaba's Wan2.1 video generator for computer vision tasks including depth estimation, segmentation, and 3D pose estimation. The model matches state-of-the-art specialized systems while training on only 7,500 synthetic videos—between 7 and 500 times less data than competing approaches.

TIIUAE has released Falcon Perception, a 0.6B-parameter early-fusion Transformer that combines image patches and text in a single sequence for open-vocabulary object grounding and segmentation. The model achieves 68.0 Macro-F1 on SA-Co (vs. 62.3 for SAM 3) and introduces PBench, a diagnostic benchmark that isolates performance across five capability levels. TIIUAE also released Falcon OCR, a 0.3B model reaching 80.3 on olmOCR and 88.6 on OmniDocBench.

Meta has released SAM 3.1, an update to its Segment Anything Model that adds Object Multiplex, a shared-memory approach for joint multi-object tracking. The new version achieves approximately 7x faster inference when tracking 128 objects on a single H100 GPU while improving video object segmentation (VOS) performance on 6 out of 7 benchmarks.