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Found 9 papers, 4 papers with code
STELLA: Continual Audio-Video Pre-training with Spatio-Temporal Localized Alignment
Continuously learning a variety of audio-video semantics over time is crucial for audio-related reasoning tasks in our ever-evolving world.
Dense Text-to-Image Generation with Attention Modulation
To address this, we propose DenseDiffusion, a training-free method that adapts a pre-trained text-to-image model to handle such dense captions while offering control over the scene layout.
Context-Preserving Two-Stage Video Domain Translation for Portrait Stylization
Portrait stylization, which translates a real human face image into an artistically stylized image, has attracted considerable interest and many prior works have shown impressive quality in recent years.
Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models
Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts.
Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models
Token-based masked generative models are gaining popularity for their fast inference time with parallel decoding.
Mutual Information Divergence: A Unified Metric for Multimodal Generative Models
Based on a recent trend that multimodal generative evaluations exploit a vison-and-language pre-trained model, we propose the negative Gaussian cross-mutual information using the CLIP features as a unified metric, coined by Mutual Information Divergence (MID).
Ranked #1 on
Human Judgment Classification
on Pascal-50S
Hallucination Pair-wise Detection (1-ref)
Hallucination Pair-wise Detection (4-ref)
+5
Contrastive Fine-grained Class Clustering via Generative Adversarial Networks
Specifically, we map the input of a generator, which was sampled from the categorical distribution, to the embedding space of the discriminator and let them act as a cluster centroid.
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
To generate future frames, we first detect keypoints of a moving object and predict future motion as a sequence of keypoints.
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Our task aims to semantically modify visual attributes of an object in an image according to the text describing the new visual appearance.
