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Found 11 papers, 5 papers with code
NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images
Recent advancements in generative models have significantly improved novel view synthesis (NVS) from multi-view data.
NovelGS: Consistent Novel-view Denoising via Large Gaussian Reconstruction Model
Specifically, by incorporating both conditional views and noisy target views, the network predicts pixel-aligned Gaussians for each view.
vTensor: Flexible Virtual Tensor Management for Efficient LLM Serving
This study introduces the vTensor, an innovative tensor structure for LLM inference based on GPU virtual memory management (VMM).
MeshSegmenter: Zero-Shot Mesh Semantic Segmentation via Texture Synthesis
Specifically, our model leverages the Segment Anything Model (SAM) model to segment the target regions from images rendered from the 3D shape.
InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models
We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability.
InstructP2P: Learning to Edit 3D Point Clouds with Text Instructions
Enhancing AI systems to perform tasks following human instructions can significantly boost productivity.
Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models
Specifically, we first generate a high-quality 3D shape from the input text in the text-to-shape stage as a 3D shape prior.
UNIF: United Neural Implicit Functions for Clothed Human Reconstruction and Animation
We propose united implicit functions (UNIF), a part-based method for clothed human reconstruction and animation with raw scans and skeletons as the input.
Taylor3DNet: Fast 3D Shape Inference With Landmark Points Based Taylor Series
Taylor3DNet exploits a set of discrete landmark points and their corresponding Taylor series coefficients to represent the implicit field of a 3D shape, and the number of landmark points is independent of the resolution of the iso-surface extraction.
OH-Former: Omni-Relational High-Order Transformer for Person Re-Identification
Transformers have shown preferable performance on many vision tasks.
Layout-Guided Novel View Synthesis from a Single Indoor Panorama
Then, we leverage the room layout prior, a strong structural constraint of the indoor scene, to guide the generation of target views.
