16 citations · 16 across the 4 of their papers we have counts for
4 papers · 1 filter
LEIA: Latent View-invariant Embeddings for Implicit 3D Articulation
Archana Swaminathan, Anubhav Gupta, Kamal Gupta +3
Neural Radiance Fields (NeRFs) have revolutionized the reconstruction of static scenes and objects in 3D, offering unprecedented quality. However, extending NeRFs to model dynamic…
Do text-free diffusion models learn discriminative visual representations?
Soumik Mukhopadhyay, Matthew Gwilliam, Yosuke Yamaguchi +6
While many unsupervised learning models focus on one family of tasks, either generative or discriminative, we explore the possibility of a unified representation learner: a model w…
Chop & Learn: Recognizing and Generating Object-State Compositions
Nirat Saini, Hanyu Wang, Archana Swaminathan +4
Recognizing and generating object-state compositions has been a challenging task, especially when generalizing to unseen compositions. In this paper, we study the task of cutting o…
Diffusion Models Beat GANs on Image Classification
Soumik Mukhopadhyay, Matthew Gwilliam, Vatsal Agarwal +5
While many unsupervised learning models focus on one family of tasks, either generative or discriminative, we explore the possibility of a unified representation learner: a model w…