MOSE: A new dataset for video object segmentation in complex scenes
Video object segmentation (VOS) aims at segmenting a particular object throughout the
entire video clip sequence. The state-of-the-art VOS methods have achieved excellent …
entire video clip sequence. The state-of-the-art VOS methods have achieved excellent …
The devil is in the labels: Noisy label correction for robust scene graph generation
Unbiased SGG has achieved significant progress over recent years. However, almost all
existing SGG models have overlooked the ground-truth annotation qualities of prevailing …
existing SGG models have overlooked the ground-truth annotation qualities of prevailing …
Reltr: Relation transformer for scene graph generation
Different objects in the same scene are more or less related to each other, but only a limited
number of these relationships are noteworthy. Inspired by Detection Transformer, which …
number of these relationships are noteworthy. Inspired by Detection Transformer, which …
Stacked hybrid-attention and group collaborative learning for unbiased scene graph generation
Abstract Scene Graph Generation, which generally follows a regular encoder-decoder
pipeline, aims to first encode the visual contents within the given image and then parse them …
pipeline, aims to first encode the visual contents within the given image and then parse them …
Sgtr: End-to-end scene graph generation with transformer
Abstract Scene Graph Generation (SGG) remains a challenging visual understanding task
due to its compositional property. Most previous works adopt a bottom-up two-stage or a …
due to its compositional property. Most previous works adopt a bottom-up two-stage or a …
Compositional feature augmentation for unbiased scene graph generation
Abstract Scene Graph Generation (SGG) aims to detect all the visual relation triplets< sub,
pred, obj> in a given image. With the emergence of various advanced techniques for better …
pred, obj> in a given image. With the emergence of various advanced techniques for better …
Fine-grained scene graph generation with data transfer
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in
images. Recent works have made a steady progress on SGG, and provide useful tools for …
images. Recent works have made a steady progress on SGG, and provide useful tools for …
Context-aware scene graph generation with seq2seq transformers
Scene graph generation is an important task in computer vision aimed at improving the
semantic understand-ing of the visual world. In this task, the model needs to detect objects …
semantic understand-ing of the visual world. In this task, the model needs to detect objects …
Devil's on the edges: Selective quad attention for scene graph generation
Scene graph generation aims to construct a semantic graph structure from an image such
that its nodes and edges respectively represent objects and their relationships. One of the …
that its nodes and edges respectively represent objects and their relationships. One of the …
[HTML][HTML] Bias in Machine Learning: A Literature Review
Bias could be defined as the tendency to be in favor or against a person or a group, thus
promoting unfairness. In computer science, bias is called algorithmic or artificial intelligence …
promoting unfairness. In computer science, bias is called algorithmic or artificial intelligence …