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Found 12 papers, 2 papers with code
Cartoon Hallucinations Detection: Pose-aware In Context Visual Learning
Large-scale Text-to-Image (TTI) models have become a common approach for generating training data in various generative fields.
Minecraft-ify: Minecraft Style Image Generation with Text-guided Image Editing for In-Game Application
In this paper, we first present the character texture generation system \textit{Minecraft-ify}, specified to Minecraft video game toward in-game application.
ToonAging: Face Re-Aging upon Artistic Portrait Style Transfer
In this paper, we introduce a novel one-stage method for face re-aging combined with portrait style transfer, executed in a single generative step.
UnionDet: Union-Level Detector Towards Real-Time Human-Object Interaction Detection
This is a major bottleneck in HOI detection inference time.
Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pretraining
Contrastive Language-Image Pretraining has emerged as a prominent approach for training vision and text encoders with uncurated image-text pairs from the web.
Expediting Contrastive Language-Image Pretraining via Self-distilled Encoders
Based on the unified text embedding space, ECLIPSE compensates for the additional computational cost of the momentum image encoder by expediting the online image encoder.
Video Face Re-Aging: Toward Temporally Consistent Face Re-Aging
Video face re-aging deals with altering the apparent age of a person to the target age in videos.
Co-attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
Graph Neural Networks (GNNs) have proven to be effective in processing and learning from graph-structured data.
Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pre-training
Contrastive Language-Image Pretraining has emerged as a prominent approach for training vision and text encoders with uncurated image-text pairs from the web.
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training
Pre-training vision-language models with contrastive objectives has shown promising results that are both scalable to large uncurated datasets and transferable to many downstream applications.
MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection
Human-Object Interaction (HOI) detection is the task of identifying a set of <human, object, interaction> triplets from an image.
HOTR: End-to-End Human-Object Interaction Detection with Transformers
Human-Object Interaction (HOI) detection is a task of identifying "a set of interactions" in an image, which involves the i) localization of the subject (i. e., humans) and target (i. e., objects) of interaction, and ii) the classification of the interaction labels.
Ranked #16 on
Human-Object Interaction Detection
on V-COCO
