99 citations · 186 across the 8 of their papers we have counts for
9 papers · 1 filter
Audio-Visual Speech Codecs: Rethinking Audio-Visual Speech Enhancement by Re-Synthesis
Karren Yang, Dejan Markovic, Steven Krenn +2
Since facial actions such as lip movements contain significant information about speech content, it is not surprising that audio-visual speech enhancement methods are more accurate…
LiP-Flow: Learning Inference-time Priors for Codec Avatars via Normalizing Flows in Latent Space
Emre Aksan, Shugao Ma, Akin Caliskan +5
Neural face avatars that are trained from multi-view data captured in camera domes can produce photo-realistic 3D reconstructions. However, at inference time, they must be driven b…
Audio- and Gaze-driven Facial Animation of Codec Avatars
Alexander Richard, Colin Lea, Shugao Ma +3
Codec Avatars are a recent class of learned, photorealistic face models that accurately represent the geometry and texture of a person in 3D (i.e., for virtual reality), and are al…
A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation
Hilde Kuehne, Alexander Richard, Juergen Gall
Action recognition has become a rapidly developing research field within the last decade. But with the increasing demand for large scale data, the need of hand annotated data for t…
Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data
Hilde Kuehne, Ahsan Iqbal, Alexander Richard +1
Action recognition is so far mainly focusing on the problem of classification of hand selected preclipped actions and reaching impressive results in this field. But with the perfor…
NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning
Alexander Richard, Hilde Kuehne, Ahsan Iqbal +1
Video learning is an important task in computer vision and has experienced increasing interest over the recent years. Since even a small amount of videos easily comprises several m…