Trending Research
Probing the 3D Awareness of Visual Foundation Models
mbanani/probe3d
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Given that such models can classify, delineate, and localize objects in 2D, we ask whether they also represent their 3D structure?
LM Transparency Tool: Interactive Tool for Analyzing Transformer Language Models
facebookresearch/llm-transparency-tool
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We present the LM Transparency Tool (LM-TT), an open-source interactive toolkit for analyzing the internal workings of Transformer-based language models.
MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators
Recent advances in Text-to-Video generation (T2V) have achieved remarkable success in synthesizing high-quality general videos from textual descriptions.
Solving Data Quality Problems with Desbordante: a Demo
However, most existing data profiling systems that focus on complex statistics do not provide proper integration with the tools used by contemporary data scientists.
Arc2Face: A Foundation Model of Human Faces
This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity than existing models.
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Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings
In the realm of security applications, biometric authentication systems play a crucial role, yet one often encounters challenges concerning privacy and security while developing one.
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
This work introduces an efficient method to scale Transformer-based Large Language Models (LLMs) to infinitely long inputs with bounded memory and computation.
Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance
fudan-generative-vision/champ
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In this study, we introduce a methodology for human image animation by leveraging a 3D human parametric model within a latent diffusion framework to enhance shape alignment and motion guidance in curernt human generative techniques.
ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback
liming-ai/ControlNet_Plus_Plus
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To this end, we propose ControlNet++, a novel approach that improves controllable generation by explicitly optimizing pixel-level cycle consistency between generated images and conditional controls.
Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues
SPSC and SDSC augment live samples into simulated attack samples by simulating spoofing clues of physical and digital attacks, respectively, which significantly improve the capability of the model to detect "unseen" attack types.
