Computer Vision

GSGAN introduces a hierarchical 3D Gaussian representation for faster, high-quality 3D model generation in GANs, achieving 100x speed improvement over existing methods.

GSDF: A novel dual-branch neural scene representation elegantly resolves the rendering-reconstruction trade-off by synergistically combining 3D Gaussian Splatting and Signed Distance Fields via mutual…

GS-Hider: A novel framework secures 3D Gaussian Splatting by embedding messages in a coupled, secured feature attribute, enabling invisible data hiding and accurate extraction.

Grid4D: A novel 4D decomposed hash encoding boosts high-fidelity dynamic Gaussian splatting, surpassing state-of-the-art models in visual quality and rendering speed.

GraphMorph: revolutionizing tubular structure extraction by morphing predicted graphs for superior topological accuracy.

This paper introduces a novel gradient-free decoder inversion method for latent diffusion models, improving efficiency and memory usage compared to existing gradient-based methods. The method is theo…

GoMatching, a novel video text spotting baseline, enhances tracking efficiency while maintaining strong recognition by integrating long- and short-term matching via a Transformer-based module and a re…

This paper introduces a goal-conditioned reinforcement learning approach that efficiently tunes photo finishing pipelines, achieving high-quality results in fewer iterations than optimization-based me…

GL-NeRF accelerates NeRF rendering by using Gauss-Laguerre quadrature, drastically reducing MLP calls without needing additional networks or data structures.

GeoNLF: Geometry-guided Pose-free Neural LiDAR Fields revolutionizes LiDAR point cloud processing by cleverly combining neural and geometric optimization for superior novel view synthesis and multi-vi…

Geometry Cloak embeds invisible perturbations in images to thwart AI-based 3D reconstruction, forcing the AI to generate identifiable patterns that act as watermarks to assert copyright.

Boosting indoor panoramic semantic segmentation, a new approach leverages geometric properties to optimize over- and under-sampled image segments for improved accuracy and robustness.

Guaranteed Manifold Clustering: Novel method provides geometric conditions ensuring accurate data grouping from nonlinear manifolds, showing competitive performance on CIFAR datasets.

GeoLRM: Generate stunning 3D models from just 21 images using a novel geometry-aware transformer, surpassing existing methods in efficiency and quality!

GenWarp generates high-quality novel image views from a single input image by using a semantic-preserving generative warping framework, outperforming existing methods.

GenRec: One diffusion model to rule both video generation and recognition!

This paper introduces a novel multi-stage generation framework for creating compositional scenes with fine-grained control by leveraging a trained diffusion model to produce individual scene component…

This research presents a novel method for robust semantic segmentation, achieving state-of-the-art results by generating coherent images with both semantic and covariate shifts and recalibrating uncer…

Balancing Alignment and Uniformity (BAU) framework improves generalizable person re-identification by mitigating the polarized effects of data augmentation, achieving state-of-the-art performance.

Generalizable Implicit Motion Modeling (GIMM) revolutionizes video frame interpolation by accurately predicting optical flows at any timestep, surpassing existing methods and achieving state-of-the-ar…