Search Results for author:
Found 7 papers, 3 papers with code
Idea-2-3D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs
The definition of an IDEA is the composition of multimodal inputs including text, image, and 3D models.
Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail
In this paper, we propose a new method called \emph{Ultraman} for fast reconstruction of textured 3D human models from a single image.
Network Embedding with Completely-imbalanced Labels
Network embedding, aiming to project a network into a low-dimensional space, is increasingly becoming a focus of network research.
Zero-Shot Feature Selection via Transferring Supervised Knowledge
Feature selection, an effective technique for dimensionality reduction, plays an important role in many machine learning systems.
RSDNE: Exploring Relaxed Similarity and Dissimilarity from Completely-imbalanced Labels for Network Embedding
To alleviate this, we propose a novel semi-supervised network embedding method, termed Relaxed Similarity and Dissimilarity Network Embedding (RSDNE).
Equivalence between LINE and Matrix Factorization
LINE [1], as an efficient network embedding method, has shown its effectiveness in dealing with large-scale undirected, directed, and/or weighted networks.
Image Tag Completion via Image-Specific and Tag-Specific Linear Sparse Reconstructions
Though widely utilized for facilitating image management, user-provided image tags are usually incomplete and insufficient to describe the whole semantic content of corresponding images, resulting in performance degradations in tag-dependent applications and thus necessitating effective tag completion methods.
