Asia
Segment Anything in 3D with NeRFs
We refer to the proposed solution as SA3D, for Segment Anything in 3D. It is only required to provide a manual segmentation prompt ( e.g., rough points) for the target object in a single view, which is used to generate its 2D mask in this view with SAM.
ViTAE: VisionTransformerAdvancedbyExploring IntrinsicInductiveBias
Alternatively,theyrequire large-scale training data and longer training schedules to learn the IB implicitly.
Domain Generalization via Model-Agnostic Learning of Semantic Features
Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker
Further, we introduce two complementary losses which explicitly regularize the semantic structure of thefeature space.
Multi-Lingual Acquisition on Multimodal Pre-training for Cross-modal Retrieval
Vision and diverse languages are important information sources in our living world.
DetNAS: Backbone Search for Object Detection
Yukang Chen, Tong Yang, Xiangyu Zhang, GAOFENG MENG, Xinyu Xiao, Jian Sun
Neural Information Processing Systems http://nips.cc/
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond
Lin Chen, Hossein Esfandiari, Gang Fu, Vahab Mirrokni
Neural Information Processing Systems http://nips.cc/