activity
20162026
most citedAttentional Pooling for Action Recognition

209 citations · 646 across the 46 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

MotiF: Making Text Count in Image Animation with Motion Focal Loss

Shijie Wang, Samaneh Azadi, Rohit Girdhar +3

Text-Image-to-Video (TI2V) generation aims to generate a video from an image following a text description, which is also referred to as text-guided image animation. Most existing m…

cs.CL2024

LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Jan Pfister, Julia Wunderle, Andreas Hotho

We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…

cs.CV2024

Human Action Anticipation: A Survey

Bolin Lai, Sam Toyer, Tushar Nagarajan +7

Predicting future human behavior is an increasingly popular topic in computer vision, driven by the interest in applications such as autonomous vehicles, digital assistants and hum…

cs.CV2024★ 8 cited

Movie Gen: A Cast of Media Foundation Models

Adam Polyak, Amit Zohar, Andrew Brown +85

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…

cs.AI2024

The Llama 3 Herd of Models

Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…

cs.CV2024

SoundingActions: Learning How Actions Sound from Narrated Egocentric Videos

Changan Chen, Kumar Ashutosh, Rohit Girdhar +2

We propose a novel self-supervised embedding to learn how actions sound from narrated in-the-wild egocentric videos. Whereas existing methods rely on curated data with known audio-…

cs.CV2024

InstanceDiffusion: Instance-level Control for Image Generation

Xudong Wang, Trevor Darrell, Sai Saketh Rambhatla +2

Text-to-image diffusion models produce high quality images but do not offer control over individual instances in the image. We introduce InstanceDiffusion that adds precise instanc…