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Found 21 papers, 10 papers with code
Learning Similarity between Scene Graphs and Images with Transformers
Scene graph generation is conventionally evaluated by (mean) Recall@K, which measures the ratio of correctly predicted triplets that appear in the ground truth.
Network-Free, Unsupervised Semantic Segmentation With Synthetic Images
We derive a method that yields highly accurate semantic segmentation maps without the use of any additional neural network, layers, manually annotated training data, or supervised training.
Disentangled Lifespan Face Synthesis
The generated face image given a target age code is expected to be age-sensitive reflected by bio-plausible transformations of shape and texture, while being identity preserving.
Spatial-Temporal Transformer for Dynamic Scene Graph Generation
Compared to the task of scene graph generation from images, it is more challenging because of the dynamic relationships between objects and the temporal dependencies between frames allowing for a richer semantic interpretation.
Text to Image Generation with Semantic-Spatial Aware GAN
Text-to-image synthesis (T2I) aims to generate photo-realistic images which are semantically consistent with the text descriptions.
Context-Aware Layout to Image Generation with Enhanced Object Appearance
We argue that these are caused by the lack of context-aware object and stuff feature encoding in their generators, and location-sensitive appearance representation in their discriminators.
Ranked #1 on
Layout-to-Image Generation
on COCO-Stuff 128x128
Exploring Dynamic Context for Multi-path Trajectory Prediction
In our framework, first, the spatial context between agents is explored by using self-attention architectures.
AMENet: Attentive Maps Encoder Network for Trajectory Prediction
Trajectory prediction is critical for applications of planning safe future movements and remains challenging even for the next few seconds in urban mixed traffic.
LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery
This strengthens the local feature invariance for the resampled features and enables detecting vehicles in an arbitrary orientation.
Image Captioning through Image Transformer
Inspired by the successes in text analysis and translation, previous work have proposed the \textit{transformer} architecture for image captioning.
FairNN- Conjoint Learning of Fair Representations for Fair Decisions
In this paper, we propose FairNN a neural network that performs joint feature representation and classification for fairness-aware learning.
MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic
In inference time, we combine the past context and motion information of the target agent with samplings of the latent variables to predict multiple realistic trajectories in the future.
NODIS: Neural Ordinary Differential Scene Understanding
Detected objects, their labels and the discovered relations can be used to construct a scene graph which provides an abstract semantic interpretation of an image.
Ranked #8 on
Scene Graph Generation
on Visual Genome
Target-Tailored Source-Transformation for Scene Graph Generation
We further explore more powerful representations by integrating language prior with the visual context in the transformation for the scene graph generation.
Security Event Recognition for Visual Surveillance
The experimental results show that the proposed approach outperforms the state-of-the-art methods and effective in recognizing complex security events.
Temporally Object-based Video Co-Segmentation
Therefore, we formulate a graphical model to select a proposal stream for each object in which the pairwise potentials consist of the appearance dissimilarity between different streams in the same video and also the similarity between the streams in different videos.
Triplet-based Deep Similarity Learning for Person Re-Identification
Moreover, we trained the model jointly on six different datasets, which differs from common practice - one model is just trained on one dataset and tested also on the same one.
Video Event Recognition and Anomaly Detection by Combining Gaussian Process and Hierarchical Dirichlet Process Models
In our framework, three levels of video events are connected by Hierarchical Dirichlet Process (HDP) model: low-level visual features, simple atomic activities, and multi-agent interactions.
Vehicle Detection in Aerial Images
Also, the focal loss function is used to substitute for conventional cross entropy loss function in both of the region proposed network and the final classifier.
Natural Language Guided Visual Relationship Detection
Most of the existing works treat this task as a pure visual classification task: each type of relationship or phrase is classified as a relation category based on the extracted visual features.
On Support Relations and Semantic Scene Graphs
In contrast to previous methods for extracting support relations, the proposed approach generates more accurate results, and does not require a pixel-wise semantic labeling of the scene.
