30 citations · 56 across the 13 of their papers we have counts for
10 papers · 1 filter
Context Diffusion: In-Context Aware Image Generation
Ivona Najdenkoska, Animesh Sinha, Abhimanyu Dubey +3
We propose Context Diffusion, a diffusion-based framework that enables image generation models to learn from visual examples presented in context. Recent work tackles such in-conte…
Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack
Xiaoliang Dai, Ji Hou, Chih-Yao Ma +23
Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face chal…
COLA: A Benchmark for Compositional Text-to-image Retrieval
Arijit Ray, Filip Radenovic, Abhimanyu Dubey +3
Compositional reasoning is a hallmark of human visual intelligence. Yet, despite the size of large vision-language models, they struggle to represent simple compositions by combini…
PACO: Parts and Attributes of Common Objects
Vignesh Ramanathan, Anmol Kalia, Vladan Petrovic +11
Object models are gradually progressing from predicting just category labels to providing detailed descriptions of object instances. This motivates the need for large datasets whic…
Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training
Filip Radenovic, Abhimanyu Dubey, Abhishek Kadian +6
Vision-language models trained with contrastive learning on large-scale noisy data are becoming increasingly popular for zero-shot recognition problems. In this paper we improve th…
Adaptive Methods for Real-World Domain Generalization
Abhimanyu Dubey, Vignesh Ramanathan, Alex Pentland +1
Invariant approaches have been remarkably successful in tackling the problem of domain generalization, where the objective is to perform inference on data distributions different f…