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Found 18 papers, 3 papers with code
Do Generalised Classifiers really work on Human Drawn Sketches?
This generalisation happens on two fronts: (i) generalisation across unknown categories (i. e., open-set), and (ii) generalisation traversing abstraction levels (i. e., good and bad sketches), both being timely challenges that remain unsolved in the sketch literature.
Freeview Sketching: View-Aware Fine-Grained Sketch-Based Image Retrieval
In this paper, we delve into the intricate dynamics of Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) by addressing a critical yet overlooked aspect -- the choice of viewpoint during sketch creation.
SketchDeco: Decorating B&W Sketches with Colour
This paper introduces a novel approach to sketch colourisation, inspired by the universal childhood activity of colouring and its professional applications in design and story-boarding.
It's All About Your Sketch: Democratising Sketch Control in Diffusion Models
This paper unravels the potential of sketches for diffusion models, addressing the deceptive promise of direct sketch control in generative AI.
You'll Never Walk Alone: A Sketch and Text Duet for Fine-Grained Image Retrieval
Two primary input modalities prevail in image retrieval: sketch and text.
Text-to-Image Diffusion Models are Great Sketch-Photo Matchmakers
This paper, for the first time, explores text-to-image diffusion models for Zero-Shot Sketch-based Image Retrieval (ZS-SBIR).
How to Handle Sketch-Abstraction in Sketch-Based Image Retrieval?
@q loss to inject that understanding into the system.
DemoCaricature: Democratising Caricature Generation with a Rough Sketch
In this paper, we democratise caricature generation, empowering individuals to effortlessly craft personalised caricatures with just a photo and a conceptual sketch.
Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes
In this paper, we democratise 3D content creation, enabling precise generation of 3D shapes from abstract sketches while overcoming limitations tied to drawing skills.
What Can Human Sketches Do for Object Detection?
In particular, we first perform independent prompting on both sketch and photo branches of an SBIR model to build highly generalisable sketch and photo encoders on the back of the generalisation ability of CLIP.
Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR
This paper advances the fine-grained sketch-based image retrieval (FG-SBIR) literature by putting forward a strong baseline that overshoots prior state-of-the-arts by ~11%.
CLIP for All Things Zero-Shot Sketch-Based Image Retrieval, Fine-Grained or Not
At the very core of our solution is a prompt learning setup.
Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings
Human sketch has already proved its worth in various visual understanding tasks (e. g., retrieval, segmentation, image-captioning, etc).
Picture that Sketch: Photorealistic Image Generation from Abstract Sketches
We further introduce specific designs to tackle the abstract nature of human sketches, including a fine-grained discriminative loss on the back of a trained sketch-photo retrieval model, and a partial-aware sketch augmentation strategy.
Democratising 2D Sketch to 3D Shape Retrieval Through Pivoting
We perform pivoting on two existing datasets, each from a distant research domain to the other: 2D sketch and photo pairs from the sketch-based image retrieval field (SBIR), and 3D shapes from ShapeNet.
SceneTrilogy: On Human Scene-Sketch and its Complementarity with Photo and Text
In this paper, we extend scene understanding to include that of human sketch.
Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches
In this paper, we push the boundary further for FSCIL by addressing two key questions that bottleneck its ubiquitous application (i) can the model learn from diverse modalities other than just photo (as humans do), and (ii) what if photos are not readily accessible (due to ethical and privacy constraints).
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
We first conducted a pilot study that revealed the secret lies in the existence of noisy strokes, but not so much of the "I can't sketch".
