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A comprehensive survey of scene graphs: Generation and application
Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …
attributes, and relationships between objects in the scene. As computer vision technology …
[HTML][HTML] Social media data for conservation science: A methodological overview
Improved understanding of human-nature interactions is crucial to conservation science and
practice, but collecting relevant data remains challenging. Recently, social media have …
practice, but collecting relevant data remains challenging. Recently, social media have …
A metaverse: Taxonomy, components, applications, and open challenges
SM Park, YG Kim - IEEE access, 2022 - ieeexplore.ieee.org
Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …
based on the social value of Generation Z that online and offline selves are not different …
Semantic communications: Principles and challenges
Semantic communication, regarded as the breakthrough beyond the Shannon paradigm,
aims at the successful transmission of semantic information conveyed by the source rather …
aims at the successful transmission of semantic information conveyed by the source rather …
Merlot reserve: Neural script knowledge through vision and language and sound
As humans, we navigate a multimodal world, building a holistic understanding from all our
senses. We introduce MERLOT Reserve, a model that represents videos jointly over time …
senses. We introduce MERLOT Reserve, a model that represents videos jointly over time …
The all-seeing project v2: Towards general relation comprehension of the open world
Abstract We present the All-Seeing Project V2: a new model and dataset designed for
understanding object relations in images. Specifically, we propose the All-Seeing Model V2 …
understanding object relations in images. Specifically, we propose the All-Seeing Model V2 …
[HTML][HTML] Cpt: Colorful prompt tuning for pre-trained vision-language models
Abstract Vision-Language Pre-training (VLP) models have shown promising capabilities in
grounding natural language in image data, facilitating a broad range of cross-modal tasks …
grounding natural language in image data, facilitating a broad range of cross-modal tasks …
Imagine that! abstract-to-intricate text-to-image synthesis with scene graph hallucination diffusion
In this work, we investigate the task of text-to-image (T2I) synthesis under the abstract-to-
intricate setting, ie, generating intricate visual content from simple abstract text prompts …
intricate setting, ie, generating intricate visual content from simple abstract text prompts …
Multi-modal knowledge graph construction and application: A survey
Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
Causal intervention for weakly-supervised semantic segmentation
We present a causal inference framework to improve Weakly-Supervised Semantic
Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by …
Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by …