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Found 10 papers, 4 papers with code
Discriminative Partial Domain Adversarial Network
Previous methods typically match the whole source domain to target domain, which causes negative transfer due to the source-negative classes in source domain that does not exist in target domain.
Fast Personalized Text-to-Image Syntheses With Attention Injection
Currently, personalized image generation methods mostly require considerable time to finetune and often overfit the concept resulting in generated images that are similar to custom concepts but difficult to edit by prompts.
SSR-Encoder: Encoding Selective Subject Representation for Subject-Driven Generation
Recent advancements in subject-driven image generation have led to zero-shot generation, yet precise selection and focus on crucial subject representations remain challenging.
CLIPVG: Text-Guided Image Manipulation Using Differentiable Vector Graphics
Considerable progress has recently been made in leveraging CLIP (Contrastive Language-Image Pre-Training) models for text-guided image manipulation.
Ghost-free High Dynamic Range Imaging via Hybrid CNN-Transformer and Structure Tensor
In this letter, we present a hybrid model consisting of a convolutional encoder and a Transformer decoder to generate ghost-free HDR images.
Learning to Kindle the Starlight
Capturing highly appreciated star field images is extremely challenging due to light pollution, the requirements of specialized hardware, and the high level of photographic skills needed.
Multimodal Image Fusion based on Hybrid CNN-Transformer and Non-local Cross-modal Attention
In this article, we present a hybrid model consisting of a convolutional encoder and a Transformer-based decoder to fuse multimodal images.
A Hybrid Labeled Multi-Bernoulli Filter With Amplitude For Tracking Fluctuating Targets
The amplitude information of target returns has been incorporated into many tracking algorithms for performance improvements.
Self-Adaptive Partial Domain Adaptation
Partial Domain adaptation (PDA) aims to solve a more practical cross-domain learning problem that assumes target label space is a subset of source label space.
Domain Adaptive YOLO for One-Stage Cross-Domain Detection
Multi-scale instance level features alignment is presented to reduce instance domain shift effectively , such as variations in object appearance and viewpoint.
