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View article: MotionCanvas: Cinematic Shot Design with Controllable Image-to-Video Generation
MotionCanvas: Cinematic Shot Design with Controllable Image-to-Video Generation Open
This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves meticulously planning both camera movements and object motio…
View article: Personalized Residuals for Concept-Driven Text-to-Image Generation
Personalized Residuals for Concept-Driven Text-to-Image Generation Open
We present personalized residuals and localized attention-guided sampling for efficient concept-driven generation using text-to-image diffusion models. Our method first represents concepts by freezing the weights of a pretrained text-condi…
View article: Modulating Pretrained Diffusion Models for Multimodal Image Synthesis
Modulating Pretrained Diffusion Models for Multimodal Image Synthesis Open
We present multimodal conditioning modules (MCM) for enabling conditional image synthesis using pretrained diffusion models. Previous multimodal synthesis works rely on training networks from scratch or fine-tuning pretrained networks, bot…
View article: Modulating Pretrained Diffusion Models for Multimodal Image Synthesis
Modulating Pretrained Diffusion Models for Multimodal Image Synthesis Open
We present multimodal conditioning modules (MCM) for enabling conditional image synthesis using pretrained diffusion models. Previous multimodal synthesis works rely on training networks from scratch or fine-tuning pretrained networks, bot…
View article: Density of States Estimation for Out-of-Distribution Detection
Density of States Estimation for Out-of-Distribution Detection Open
Perhaps surprisingly, recent studies have shown probabilistic model likelihoods have poor specificity for out-of-distribution (OOD) detection and often assign higher likelihoods to OOD data than in-distribution data. To ameliorate this iss…
View article: Automatic Differentiation Variational Inference with Mixtures
Automatic Differentiation Variational Inference with Mixtures Open
Automatic Differentiation Variational Inference (ADVI) is a useful tool for efficiently learning probabilistic models in machine learning. Generally approximate posteriors learned by ADVI are forced to be unimodal in order to facilitate us…
View article: ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging Open
Grasping and manipulating objects is an important human skill. Since hand-object contact is fundamental to grasping, capturing it can lead to important insights. However, observing contact through external sensors is challenging because of…
View article: The sketchy database
The sketchy database Open
We present the Sketchy database , the first large-scale collection of sketch-photo pairs. We ask crowd workers to sketch particular photographic objects sampled from 125 categories and acquire 75,471 sketches of 12,500 objects. The Sketchy…