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Found 11 papers, 1 papers with code
SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer
Recent advances in 2D/3D generative models enable the generation of dynamic 3D objects from a single-view video.
3D Object Detection from Point Cloud via Voting Step Diffusion
In this work, we focus on the distributional properties of point clouds and formulate the voting process as generating new points in the high-density region of the distribution of object centers.
External Knowledge Enhanced 3D Scene Generation from Sketch
Generating realistic 3D scenes is challenging due to the complexity of room layouts and object geometries. We propose a sketch based knowledge enhanced diffusion architecture (SEK) for generating customized, diverse, and plausible 3D scenes.
Beyond Skeletons: Integrative Latent Mapping for Coherent 4D Sequence Generation
To address this, we propose a novel framework that generates coherent 4D sequences with animation of 3D shapes under given conditions with dynamic evolution of shape and color over time through integrative latent mapping.
Enhancing Scene Text Detectors with Realistic Text Image Synthesis Using Diffusion Models
We contend that one main limitation of existing generation methods is the insufficient integration of foreground text with the background.
SingleInsert: Inserting New Concepts from a Single Image into Text-to-Image Models for Flexible Editing
To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper embedding that aligns with the semantic space of the T2I model.
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation
In this paper, we propose a sketch and text guided probabilistic diffusion model for colored point cloud generation that conditions the denoising process jointly with a hand drawn sketch of the object and its textual description.
Learning in a Single Domain for Non-Stationary Multi-Texture Synthesis
To our knowledge, ours is the first scheme for this challenging task, including model, training, and evaluation.
3D Spatial Multimodal Knowledge Accumulation for Scene Graph Prediction in Point Cloud
In-depth understanding of a 3D scene not only involves locating/recognizing individual objects, but also requires to infer the relationships and interactions among them.
CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer
CCPL can preserve the coherence of the content source during style transfer without degrading stylization.
Minimum Potential Energy of Point Cloud for Robust Global Registration
Different from the most existing point set registration methods which usually extract the descriptors to find correspondences between point sets, our proposed MPE alignment method is able to handle large scale raw data offset without depending on traditional descriptors extraction, whether for the local or global registration methods.
