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Found 16 papers, 5 papers with code
Gaussian Masked Autoencoders
Our approach, named Gaussian Masked Autoencoder, or GMAE, aims to learn semantic abstractions and spatial understanding jointly.
Synergy and Synchrony in Couple Dances
Our contributions are a demonstration of the advantages of socially conditioned future motion prediction and an in-the-wild, couple dance video dataset to enable future research in this direction.
KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models
This paper investigates visual analogical reasoning in large multimodal models (LMMs) compared to human adults and children.
Diffusion Models as Data Mining Tools
Concretely, we show that after finetuning conditional diffusion models to synthesize images from a specific dataset, we can use these models to define a typicality measure on that dataset.
Pose Priors from Language Models
We present a zero-shot pose optimization method that enforces accurate physical contact constraints when estimating the 3D pose of humans.
Can Language Models Learn to Listen?
We present a framework for generating appropriate facial responses from a listener in dyadic social interactions based on the speaker's words.
Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion
We present a framework for modeling interactional communication in dyadic conversations: given multimodal inputs of a speaker, we autoregressively output multiple possibilities of corresponding listener motion.
Strumming to the Beat: Audio-Conditioned Contrastive Video Textures
We learn representations for video frames and frame-to-frame transition probabilities by fitting a video-specific model trained using contrastive learning.
Contrastive Video Textures
By randomly traversing edges with high transition probabilities, we generate diverse temporally smooth videos with novel sequences and transitions.
Learning to Factorize and Relight a City
We propose a learning-based framework for disentangling outdoor scenes into temporally-varying illumination and permanent scene factors.
Body2Hands: Learning to Infer 3D Hands from Conversational Gesture Body Dynamics
We demonstrate the efficacy of our method on hand gesture synthesis from body motion input, and as a strong body prior for single-view image-based 3D hand pose estimation.
Learning Individual Styles of Conversational Gesture
Specifically, we perform cross-modal translation from "in-the-wild'' monologue speech of a single speaker to their hand and arm motion.
Ranked #4 on
Gesture Generation
on BEAT
Everybody Dance Now
This paper presents a simple method for "do as I do" motion transfer: given a source video of a person dancing, we can transfer that performance to a novel (amateur) target after only a few minutes of the target subject performing standard moves.
Photographic home styles in Congress: a computer vision approach
While members of Congress now routinely communicate with constituents using images on a variety of internet platforms, little is known about how images are used as a means of strategic political communication.
A Century of Portraits: A Visual Historical Record of American High School Yearbooks
4) A new method for discovering and displaying the visual elements used by the CNN-based date-prediction model to date portraits, finding that they correspond to the tell-tale fashions of each era.
Detecting People in Cubist Art
Although the human visual system is surprisingly robust to extreme distortion when recognizing objects, most evaluations of computer object detection methods focus only on robustness to natural form deformations such as people's pose changes.
