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cs.CV2024
MTA-CLIP: Language-Guided Semantic Segmentation with Mask-Text Alignment
Anurag Das, Xinting Hu, Li Jiang +1
Recent approaches have shown that large-scale vision-language models such as CLIP can improve semantic segmentation performance. These methods typically aim for pixel-level vision-…
cs.CV2024
Improving 2D Feature Representations by 3D-Aware Fine-Tuning
Yuanwen Yue, Anurag Das, Francis Engelmann +2
Current visual foundation models are trained purely on unstructured 2D data, limiting their understanding of 3D structure of objects and scenes. In this work, we show that fine-tun…