Concerns with enabling computers to interpret and understand visual inputs, such as images and videos.
The article presents SCEdit, a generative tuning framework for image diffusion models used in tasks like text-to-image generation and controllable image synthesis. This framework focuses on the role of skip…
Continue readingThe MAG-Edit method enables localized image editing in complex scenarios. This training-free, inference-stage optimization method optimizes the noise latent feature in diffusion models by maximizing two mask-based cross-attention constraints of…
Continue readingPolyDiff is the first diffusion-based approach capable of directly generating realistic and diverse 3D polygonal meshes. Unlike methods that use alternate 3D shape representations, PolyDiff operates natively on the polygonal…
Continue readingThis article presents a new image inversion architecture that extracts high-rate latent features for image editing with StyleGAN models. The authors discuss the challenges of image editing with pretrained GAN…
Continue readingThis research paper presents a language-assisted approach to point cloud feature learning (LAST-PCL), aimed at improving 3D scene understanding. The approach incorporates knowledge from other modalities, like images and text,…
Continue readingThe article proposes a method named GauFRe for dynamic scene reconstruction using deformable 3D Gaussians, specifically designed for monocular video. The method extends the efficiency of Gaussian Splatting to accommodate…
Continue readingThis research introduces a 3D volumetric encoder for efficient and flexible text-to-3D generation. A lightweight network is developed to acquire feature volumes from multi-view images, which are then trained on…
Continue readingThe article presents GAvatar, a method for generating high-fidelity 3D avatars from text prompts. The method utilizes a new 3D representation, 3D Gaussian Splatting, to create realistic, animatable avatars. The…
Continue readingThis paper presents a new approach for segmenting and tracking moving objects in complex visual scenes. The method is based on refining optical flow predictions using appearance-based information. It employs…
Continue readingThe academic article introduces a new multimodal model that can understand arbitrary visual prompts, enabling users to intuitively mark images using natural cues like a red bounding box or pointed…
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