115 citations · 217 across the 7 of their papers we have counts for
11 papers
CAFE: Confining Feature Distillation to Language-Routed Adapters for Compact Multilingual Automatic Speech Recognition
Tianchi Liu, Nicholas Moratelli, Khurram Azeem Hashmi +5
Feature distillation is usually expected to add to logit distillation. We find that this expectation does not hold for two common feature losses in compact multilingual automatic s…
VisionPsy-Nano: Improving Accuracy, Efficiency, and Reliability in On-Device Vision-Language Models
Khurram Azeem Hashmi, Mohammadreza Zolfaghari, Changdae Park +6
Sub-billion-parameter Vision-Language Models are increasingly viable for on-device deployment, yet compact model size alone does not guarantee usability. On a phone, such a model c…
StorySync: Training-Free Subject Consistency in Text-to-Image Generation via Region Harmonization
Gopalji Gaur, Mohammadreza Zolfaghari, Thomas Brox
Generating a coherent sequence of images that tells a visual story, using text-to-image diffusion models, often faces the critical challenge of maintaining subject consistency acro…
CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations
Mohammadreza Zolfaghari, Yi Zhu, Peter Gehler +1
Contrastive learning allows us to flexibly define powerful losses by contrasting positive pairs from sets of negative samples. Recently, the principle has also been used to learn c…
A Comprehensive Study of Deep Video Action Recognition
Yi Zhu, Xinyu Li, Chunhui Liu +7
Video action recognition is one of the representative tasks for video understanding. Over the last decade, we have witnessed great advancements in video action recognition thanks t…
COOT: Cooperative Hierarchical Transformer for Video-Text Representation Learning
Simon Ging, Mohammadreza Zolfaghari, Hamed Pirsiavash +1
Many real-world video-text tasks involve different levels of granularity, such as frames and words, clip and sentences or videos and paragraphs, each with distinct semantics. In th…
Temporal Shift GAN for Large Scale Video Generation
Andres Munoz, Mohammadreza Zolfaghari, Max Argus +1
Video generation models have become increasingly popular in the last few years, however the standard 2D architectures used today lack natural spatio-temporal modelling capabilities…
Learning Representations for Predicting Future Activities
Mohammadreza Zolfaghari, Özgün Çiçek, Syed Mohsin Ali +3
Foreseeing the future is one of the key factors of intelligence. It involves understanding of the past and current environment as well as decent experience of its possible dynamics…
ECO: Efficient Convolutional Network for Online Video Understanding
Mohammadreza Zolfaghari, Kamaljeet Singh, Thomas Brox
The state of the art in video understanding suffers from two problems: (1) The major part of reasoning is performed locally in the video, therefore, it misses important relationshi…
Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection
Mohammadreza Zolfaghari, Gabriel L. Oliveira, Nima Sedaghat +1
General human action recognition requires understanding of various visual cues. In this paper, we propose a network architecture that computes and integrates the most important vis…
Orientation-boosted Voxel Nets for 3D Object Recognition
Nima Sedaghat, Mohammadreza Zolfaghari, Ehsan Amiri +1
Recent work has shown good recognition results in 3D object recognition using 3D convolutional networks. In this paper, we show that the object orientation plays an important role…