Zobrazeno 1 - 10
of 585
pro vyhledávání: '"Mitra, Niloy"'
Differentiable rendering is a key ingredient for inverse rendering and machine learning, as it allows to optimize scene parameters (shape, materials, lighting) to best fit target images. Differentiable rendering requires that each scene parameter rel
Externí odkaz:
http://arxiv.org/abs/2409.01421
We introduce a theoretical and practical framework for efficient importance sampling of mini-batch samples for gradient estimation from single and multiple probability distributions. To handle noisy gradients, our framework dynamically evolves the im
Externí odkaz:
http://arxiv.org/abs/2407.15525
Autor:
Muralikrishnan, Sanjeev, Dutt, Niladri Shekhar, Chaudhuri, Siddhartha, Aigerman, Noam, Kim, Vladimir, Fisher, Matthew, Mitra, Niloy J.
We introduce Temporal Residual Jacobians as a novel representation to enable data-driven motion transfer. Our approach does not assume access to any rigging or intermediate shape keyframes, produces geometrically and temporally consistent motions, an
Externí odkaz:
http://arxiv.org/abs/2407.14958
Autor:
Williamson, Romy, Mitra, Niloy J.
Neural surfaces (e.g., neural map encoding, deep implicits and neural radiance fields) have recently gained popularity because of their generic structure (e.g., multi-layer perceptron) and easy integration with modern learning-based setups. Tradition
Externí odkaz:
http://arxiv.org/abs/2407.07755
Autor:
Shen, Yuan, Ceylan, Duygu, Guerrero, Paul, Xu, Zexiang, Mitra, Niloy J., Wang, Shenlong, Frühstück, Anna
We present a simple, modular, and generic method that upsamples coarse 3D models by adding geometric and appearance details. While generative 3D models now exist, they do not yet match the quality of their counterparts in image and video domains. We
Externí odkaz:
http://arxiv.org/abs/2406.00609
We present a method to build animatable dog avatars from monocular videos. This is challenging as animals display a range of (unpredictable) non-rigid movements and have a variety of appearance details (e.g., fur, spots, tails). We develop an approac
Externí odkaz:
http://arxiv.org/abs/2403.17103
Autor:
Karnewar, Animesh, Shapovalov, Roman, Monnier, Tom, Vedaldi, Andrea, Mitra, Niloy J., Novotny, David
Encoding information from 2D views of an object into a 3D representation is crucial for generalized 3D feature extraction. Such features can then enable 3D reconstruction, 3D generation, and other applications. We propose GOEmbed (Gradient Origin Emb
Externí odkaz:
http://arxiv.org/abs/2312.08744
We present LooseControl to allow generalized depth conditioning for diffusion-based image generation. ControlNet, the SOTA for depth-conditioned image generation, produces remarkable results but relies on having access to detailed depth maps for guid
Externí odkaz:
http://arxiv.org/abs/2312.03079
Autor:
Pandey, Karran, Guerrero, Paul, Gadelha, Matheus, Hold-Geoffroy, Yannick, Singh, Karan, Mitra, Niloy
Diffusion Handles is a novel approach to enabling 3D object edits on diffusion images. We accomplish these edits using existing pre-trained diffusion models, and 2D image depth estimation, without any fine-tuning or 3D object retrieval. The edited re
Externí odkaz:
http://arxiv.org/abs/2312.02190
Pretrained vision language models (VLMs) present an opportunity to caption unlabeled 3D objects at scale. The leading approach to summarize VLM descriptions from different views of an object (Luo et al., 2023) relies on a language model (GPT4) to pro
Externí odkaz:
http://arxiv.org/abs/2311.17851