In the last few years, Neural Painting (NP) techniques became capable of...
Have you ever imagined how it would look if we placed new objects into
p...
Whole-body biometric recognition is an important area of research due to...
Text-to-image (T2I) research has grown explosively in the past year, owi...
Recently, CLIP-guided image synthesis has shown appealing performance on...
Wires and powerlines are common visual distractions that often undermine...
The unlearning problem of deep learning models, once primarily an academ...
Image editing using diffusion models has witnessed extremely fast-paced
...
Recent text-to-video generation approaches rely on computationally heavy...
We present a novel graph Transformer generative adversarial network (GTG...
The recent advances in diffusion models have set an impressive milestone...
Image generation has been a long sought-after but challenging task, and
...
Image completion with large-scale free-form missing regions is one of th...
Transformers are quickly becoming one of the most heavily applied deep
l...
Recent research has revealed that reducing the temporal and spatial
redu...
Deep image inpainting has made impressive progress with recent advances ...
Despite the popularity of Model Compression and Multitask Learning, how ...
Image rasterization is a mature technique in computer graphics, while im...
Despite the rapid development of Neural Radiance Field (NeRF), the neces...
Point-based object localization (POL), which pursues high-performance ob...
Recent works have shown that the computational efficiency of video
recog...
Efficient video architecture is the key to deploying video recognition
s...
The goal of unpaired image-to-image translation is to produce an output ...
Reading to act is a prevalent but challenging task which requires the ab...
This work targets designing a principled and unified training-free frame...
Post-training quantization methods use a set of calibration data to comp...
Tracking segmentation masks of multiple instances has been intensively
s...
The recent success of NeRF and other related implicit neural representat...
Retinal vessel segmentation from retinal images is an essential task for...
While recent studies on semi-supervised learning have shown remarkable
p...
Object re-identification (ReID) is a key application of city-scale camer...
Video instance segmentation is a complex task in which we need to detect...
Text segmentation is a prerequisite in many real-world text-related task...
We study the problem of concept induction in visual reasoning, i.e.,
ide...
Human-object interaction detection is a relatively new task in the world...
The development of practical applications, such as autonomous driving an...
The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...
Image matting is a key technique for image and video editing and composi...
Cardiac motion estimation plays a key role in MRI cardiac feature tracki...
Deep convolution-based single image super-resolution (SISR) networks emb...