198 citations · 617 across the 20 of their papers we have counts for
7 papers · 1 filter
Cross-Modal Contrastive Learning for Robust Reasoning in VQA
Qi Zheng, Chaoyue Wang, Daqing Liu +2
Multi-modal reasoning in visual question answering (VQA) has witnessed rapid progress recently. However, most reasoning models heavily rely on shortcuts learned from training data,…
TransVG++: End-to-End Visual Grounding with Language Conditioned Vision Transformer
Jiajun Deng, Zhengyuan Yang, Daqing Liu +5
In this work, we explore neat yet effective Transformer-based frameworks for visual grounding. The previous methods generally address the core problem of visual grounding, i.e., mu…
Modeling Image Composition for Complex Scene Generation
Zuopeng Yang, Daqing Liu, Chaoyue Wang +2
We present a method that achieves state-of-the-art results on challenging (few-shot) layout-to-image generation tasks by accurately modeling textures, structures and relationships…
SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders
Gang Li, Heliang Zheng, Daqing Liu +3
Recently, significant progress has been made in masked image modeling to catch up to masked language modeling. However, unlike words in NLP, the lack of semantic decomposition of i…
Importance Weighted Structure Learning for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
Scene graph generation is a structured prediction task aiming to explicitly model objects and their relationships via constructing a visually-grounded scene graph for an input imag…
Constrained Structure Learning for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
As a structured prediction task, scene graph generation aims to build a visually-grounded scene graph to explicitly model objects and their relationships in an input image. Current…