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Found 11 papers, 6 papers with code
Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis
In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data.
Ranked #1 on
Sketch-to-Image Translation
on Scribble
PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters
We propose PAniC-3D, a system to reconstruct stylized 3D character heads directly from illustrated (p)ortraits of (ani)me (c)haracters.
Anatomy-aware 3D Human Pose Estimation with Bone-based Pose Decomposition
In this work, we propose a new solution to 3D human pose estimation in videos.
Ranked #12 on
Monocular 3D Human Pose Estimation
on Human3.6M
Sample-efficient Multi-objective Molecular Optimization with GFlowNets
Many crucial scientific problems involve designing novel molecules with desired properties, which can be formulated as a black-box optimization problem over the discrete chemical space.
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
However, limited attention is paid to hierarchical generative models, which can exploit the inherent hierarchical structure (with rich semantic information) of the molecular graphs and generate complex molecules of larger size that we shall demonstrate to be difficult for most existing models.
Making Pre-trained Language Models Great on Tabular Prediction
Condensing knowledge from diverse domains, language models (LMs) possess the capability to comprehend feature names from various tables, potentially serving as versatile learners in transferring knowledge across distinct tables and diverse prediction tasks, but their discrete text representation space is inherently incompatible with numerical feature values in tables.
Learning Progressive Joint Propagation for Human Motion Prediction
Last, in order to incorporate a general motion space for high-quality prediction, we build a memory-based dictionary, which aims to preserve the global motion patterns in training data to guide the predictions.
A Unified 3D Human Motion Synthesis Model via Conditional Variational Auto-Encoder
Notably, by considering this problem as a conditional generation process, we estimate a parametric distribution of the missing regions based on the input conditions, from which to sample and synthesize the full motion series.
GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels
Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation burden.
Generative AI for Controllable Protein Sequence Design: A Survey
To set the stage, we first outline the foundational tasks in protein sequence design in terms of the constraints involved and present key generative models and optimization algorithms.
Dr3: Ask Large Language Models Not to Give Off-Topic Answers in Open Domain Multi-Hop Question Answering
To alleviate this issue, we propose the Discriminate->Re-Compose->Re- Solve->Re-Decompose (Dr3) mechanism.
