5 papers · 1 filter
A Mixed Diet Makes DINO An Omnivorous Vision Encoder
Rishabh Kabra, Maks Ovsjanikov, Drew A. Hudson +5
Pre-trained vision encoders like DINOv2 have demonstrated exceptional performance on unimodal tasks. However, we observe that their features are poorly aligned across different vis…
TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment
Bingyi Cao, Koert Chen, Kevis-Kokitsi Maninis +16
Recent progress in vision-language pretraining has enabled significant improvements to many downstream computer vision applications, such as classification, retrieval, segmentation…
AlignDiff: Learning Physically-Grounded Camera Alignment via Diffusion
Liuyue Xie, Jiancong Guo, Ozan Cakmakci +3
Accurate camera calibration is a fundamental task for 3D perception, especially when dealing with real-world, in-the-wild environments where complex optical distortions are common.…
TIPS: Text-Image Pretraining with Spatial awareness
Kevis-Kokitsi Maninis, Kaifeng Chen, Soham Ghosh +11
While image-text representation learning has become very popular in recent years, existing models tend to lack spatial awareness and have limited direct applicability for dense und…
XFeat: Accelerated Features for Lightweight Image Matching
Guilherme Potje, Felipe Cadar, Andre Araujo +2
We introduce a lightweight and accurate architecture for resource-efficient visual correspondence. Our method, dubbed XFeat (Accelerated Features), revisits fundamental design choi…