View selection for 3d captioning via diffusion ranking
Scalable annotation approaches are crucial for constructing extensive 3D-text datasets,
facilitating a broader range of applications. However, existing methods sometimes lead to …
facilitating a broader range of applications. However, existing methods sometimes lead to …
Representation alignment for generation: Training diffusion transformers is easier than you think
Recent studies have shown that the denoising process in (generative) diffusion models can
induce meaningful (discriminative) representations inside the model, though the quality of …
induce meaningful (discriminative) representations inside the model, though the quality of …
Deconstructing denoising diffusion models for self-supervised learning
In this study, we examine the representation learning abilities of Denoising Diffusion Models
(DDM) that were originally purposed for image generation. Our philosophy is to deconstruct …
(DDM) that were originally purposed for image generation. Our philosophy is to deconstruct …
Diffusion-ss3d: Diffusion model for semi-supervised 3d object detection
Semi-supervised object detection is crucial for 3D scene understanding, efficiently
addressing the limitation of acquiring large-scale 3D bounding box annotations. Existing …
addressing the limitation of acquiring large-scale 3D bounding box annotations. Existing …
Diffusion models and representation learning: A survey
Diffusion Models are popular generative modeling methods in various vision tasks, attracting
significant attention. They can be considered a unique instance of self-supervised learning …
significant attention. They can be considered a unique instance of self-supervised learning …
Ecg synthesis via diffusion-based state space augmented transformer
Cardiovascular diseases (CVDs) are a major global health concern, causing significant
morbidity and mortality. AI's integration with healthcare offers promising solutions, with data …
morbidity and mortality. AI's integration with healthcare offers promising solutions, with data …
Image understanding makes for a good tokenizer for image generation
Modern image generation (IG) models have been shown to capture rich semantics valuable
for image understanding (IU) tasks. However, the potential of IU models to improve IG …
for image understanding (IU) tasks. However, the potential of IU models to improve IG …
Diff3DETR: Agent-Based Diffusion Model for Semi-supervised 3D Object Detection
Abstract 3D object detection is essential for understanding 3D scenes. Contemporary
techniques often require extensive annotated training data, yet obtaining point-wise …
techniques often require extensive annotated training data, yet obtaining point-wise …
Balancing Act: Distribution-Guided Debiasing in Diffusion Models
Abstract Diffusion Models (DMs) have emerged as powerful generative models with
unprecedented image generation capability. These models are widely used for data …
unprecedented image generation capability. These models are widely used for data …
ToDA: Target-oriented Diffusion Attacker against Recommendation System
Recommendation systems (RS) have become indispensable tools for web services to
address information overload, thus enhancing user experiences and bolstering platforms' …
address information overload, thus enhancing user experiences and bolstering platforms' …