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Found 14 papers, 4 papers with code
Towards Physical Understanding in Video Generation: A 3D Point Regularization Approach
Furthermore, our model improves the overall quality of video generation by promoting the 3D consistency of moving objects and reducing abrupt changes in shape and motion.
Wonderland: Navigating 3D Scenes from a Single Image
Specifically, we introduce a large-scale reconstruction model that uses latents from a video diffusion model to predict 3D Gaussian Splattings for the scenes in a feed-forward manner.
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training
For the first time, our model SnapGen, demonstrates the generation of 1024x1024 px images on a mobile device around 1. 4 seconds.
Ranked #11 on
Text-to-Image Generation
on GenEval
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
Neural network architecture design requires making many crucial decisions.
ControlMM: Controllable Masked Motion Generation
To further enhance control precision, we introduce inference-time logit editing, which manipulates the predicted conditional motion distribution so that the generated motion, sampled from the adjusted distribution, closely adheres to the input control signals.
Lightweight Predictive 3D Gaussian Splats
Our key observation is that nearby points in the scene can share similar representations.
4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models
We then learn the canonical 3D representation of the video using a freeze-time video, delicately generated from the reference video.
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model
Diffusion-based image generation models have achieved great success in recent years by showing the capability of synthesizing high-quality content.
AToM: Amortized Text-to-Mesh using 2D Diffusion
We introduce Amortized Text-to-Mesh (AToM), a feed-forward text-to-mesh framework optimized across multiple text prompts simultaneously.
Diffusion Priors for Dynamic View Synthesis from Monocular Videos
Dynamic novel view synthesis aims to capture the temporal evolution of visual content within videos.
Real-Time Neural Light Field on Mobile Devices
Nevertheless, to reach a similar rendering quality as NeRF, the network in NeLF is designed with intensive computation, which is not mobile-friendly.
Deep learning model trained on mobile phone-acquired frozen section images effectively detects basal cell carcinoma
Results: The model uses an image as input and produces a 2-dimensional black and white output of prediction of the same dimension; the areas determined to be basal cell carcinoma were displayed with white color, in a black background.
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data
We investigate the effectiveness of a simple solution to the common problem of deep learning in medical image analysis with limited quantities of labeled training data.
