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Found 7 papers, 4 papers with code
COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design
Our COLE system comprises multiple fine-tuned Large Language Models (LLMs), Large Multimodal Models (LMMs), and Diffusion Models (DMs), each specifically tailored for design-aware layer-wise captioning, layout planning, reasoning, and the task of generating images and text.
EMEF: Ensemble Multi-Exposure Image Fusion
In the second stage, we tune the imitator network by optimizing the style code, in order to find an optimal fusion result for each input pair.
MusicFace: Music-driven Expressive Singing Face Synthesis
In this paper, we present a method for this task with natural motions of the lip, facial expression, head pose, and eye states.
MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining
Second, masked self-distillation is also consistent with vision-language contrastive from the perspective of training objective as both utilize the visual encoder for feature aligning, and thus is able to learn local semantics getting indirect supervision from the language.
I^2R-Net: Intra- and Inter-Human Relation Network for Multi-Person Pose Estimation
In this paper, we present the Intra- and Inter-Human Relation Networks (I^2R-Net) for Multi-Person Pose Estimation.
Ranked #2 on
Multi-Person Pose Estimation
on OCHuman
General Facial Representation Learning in a Visual-Linguistic Manner
In this paper, we study the transfer performance of pre-trained models on face analysis tasks and introduce a framework, called FaRL, for general Facial Representation Learning in a visual-linguistic manner.
Ranked #1 on
Face Parsing
on CelebAMask-HQ
(using extra training data)
Exploring Temporal Coherence for More General Video Face Forgery Detection
The first stage is a fully temporal convolution network (FTCN).
Ranked #4 on
DeepFake Detection
on FakeAVCeleb
