Search Results for author:
Found 21 papers, 6 papers with code
DiffusionLight: Light Probes for Free by Painting a Chrome Ball
To address this problem, we leverage diffusion models trained on billions of standard images to render a chrome ball into the input image.
SwapNet: Garment Transfer in Single View Images
Garment transfer is a challenging task that requires (i) disentangling the features of the clothing from the body pose and shape and (ii) realistic synthesis of the garment texture on the new body.
Ranked #1 on
Virtual Try-on
on FashionIQ
(using extra training data)
TextureGAN: Controlling Deep Image Synthesis with Texture Patches
In this paper, we investigate deep image synthesis guided by sketch, color, and texture.
Ranked #2 on
Image Reconstruction
on Edge-to-Shoes
Probing the 3D Awareness of Visual Foundation Models
Given that such models can classify, delineate, and localize objects in 2D, we ask whether they also represent their 3D structure?
Kernel Mean Matching for Content Addressability of GANs
We propose a novel procedure which adds "content-addressability" to any given unconditional implicit model e. g., a generative adversarial network (GAN).
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
The first technique involves the incorporation of Heavy Ball (HB) momentum, a well-known technique for improving optimization, into existing diffusion numerical methods to expand their stability regions.
Deep Forward and Inverse Perceptual Models for Tracking and Prediction
We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics.
ANR: Articulated Neural Rendering for Virtual Avatars
The combination of traditional rendering with neural networks in Deferred Neural Rendering (DNR) provides a compelling balance between computational complexity and realism of the resulting images.
PVA: Pixel-aligned Volumetric Avatars
Volumetric models typically employ a global code to represent facial expressions, such that they can be driven by a small set of animation parameters.
Pixel-Aligned Volumetric Avatars
Volumetric models typically employ a global code to represent facial expressions, such that they can be driven by a small set of animation parameters.
Ranked #5 on
Generalizable Novel View Synthesis
on ZJU-MoCap
DRaCoN -- Differentiable Rasterization Conditioned Neural Radiance Fields for Articulated Avatars
In this work, we present, DRaCoN, a framework for learning full-body volumetric avatars which exploits the advantages of both the 2D and 3D neural rendering techniques.
DreamBooth3D: Subject-Driven Text-to-3D Generation
We present DreamBooth3D, an approach to personalize text-to-3D generative models from as few as 3-6 casually captured images of a subject.
LANe: Lighting-Aware Neural Fields for Compositional Scene Synthesis
Specifically, we learn a scene representation that disentangles the static background and transient elements into a world-NeRF and class-specific object-NeRFs to allow compositional synthesis of multiple objects in the scene.
MAGMA: Music Aligned Generative Motion Autodecoder
Mapping music to dance is a challenging problem that requires spatial and temporal coherence along with a continual synchronization with the music's progression.
Which way is `right'?: Uncovering limitations of Vision-and-Language Navigation model
The challenging task of Vision-and-Language Navigation (VLN) requires embodied agents to follow natural language instructions to reach a goal location or object (e. g. `walk down the hallway and turn left at the piano').
Dress-Me-Up: A Dataset & Method for Self-Supervised 3D Garment Retargeting
We propose a novel self-supervised framework for retargeting non-parameterized 3D garments onto 3D human avatars of arbitrary shapes and poses, enabling 3D virtual try-on (VTON).
SHINOBI: Shape and Illumination using Neural Object Decomposition via BRDF Optimization In-the-wild
We present SHINOBI, an end-to-end framework for the reconstruction of shape, material, and illumination from object images captured with varying lighting, pose, and background.
Lumiere: A Space-Time Diffusion Model for Video Generation
We introduce Lumiere -- a text-to-video diffusion model designed for synthesizing videos that portray realistic, diverse and coherent motion -- a pivotal challenge in video synthesis.
Ranked #6 on
Text-to-Video Generation
on UCF-101
WordRobe: Text-Guided Generation of Textured 3D Garments
We achieve this by first learning a latent representation of 3D garments using a novel coarse-to-fine training strategy and a loss for latent disentanglement, promoting better latent interpolation.
3D Congealing: 3D-Aware Image Alignment in the Wild
The framework optimizes for the canonical representation together with the pose for each input image, and a per-image coordinate map that warps 2D pixel coordinates to the 3D canonical frame to account for the shape matching.
MagicMirror: Fast and High-Quality Avatar Generation with a Constrained Search Space
We introduce a novel framework for 3D human avatar generation and personalization, leveraging text prompts to enhance user engagement and customization.
