4 accepted papers
Vision foundation models have shown great promise for open-set 3D object retrieval (3DOR) through efficient adaptation to multi-view images. Leveraging semantically aligned latent space, previous work typically adapts the CLIP encoder to build view-based 3D descriptors. Despite CLIP's strong general
Understanding the generalization behavior of in-context learning (ICL) in Transformers remains a fundamental challenge, as most existing theoretical analyses are based on the assumption that data are independently and identically distributed (i.i.d.), an assumption that often does not hold in practi
In this paper, we propose the novel complementary Siamese networks (CoSNet) for visual tracking by exploiting complementary global and local representations to learn a matching function. In specific, the proposed CoSNet is two-fold: a global Siamese network (GSNet) and a local Siamese network (LSNet…
In this paper, we exploit deep convolutional features for object appearance modeling and propose a simple while effective deep discriminative model (DDM) for visual tracking. The proposed DDM takes as input the deep features and outputs an object-background confidence map. Considering that both spat…