Zobrazeno 1 - 10
of 244
pro vyhledávání: '"Lee, Sangyoun"'
Recently, significant improvements in rate-distortion performance of image compression have been achieved with deep-learning techniques. A key factor in this success is the use of additional bits to predict an approximation of the latent vector, whic
Externí odkaz:
http://arxiv.org/abs/2409.12719
Propagation-based video inpainting using optical flow at the pixel or feature level has recently garnered significant attention. However, it has limitations such as the inaccuracy of optical flow prediction and the propagation of noise over time. The
Externí odkaz:
http://arxiv.org/abs/2408.11402
All current benchmarks for multimodal deepfake detection manipulate entire frames using various generation techniques, resulting in oversaturated detection accuracies exceeding 94% at the video-level classification. However, these benchmarks struggle
Externí odkaz:
http://arxiv.org/abs/2408.02954
Temporal Action Localization (TAL) is a critical task in video analysis, identifying precise start and end times of actions. Existing methods like CNNs, RNNs, GCNs, and Transformers have limitations in capturing long-range dependencies and temporal c
Externí odkaz:
http://arxiv.org/abs/2407.13078
Autor:
Cho, Suhwan, Lee, Minhyeok, Lee, Jungho, Kim, Donghyeong, Lee, Seunghoon, Woo, Sungmin, Lee, Sangyoun
Unsupervised video object segmentation (VOS), also known as video salient object detection, aims to detect the most prominent object in a video at the pixel level. Recently, two-stream approaches that leverage both RGB images and optical flow maps ha
Externí odkaz:
http://arxiv.org/abs/2407.11714
Self-supervised multi-frame monocular depth estimation relies on the geometric consistency between successive frames under the assumption of a static scene. However, the presence of moving objects in dynamic scenes introduces inevitable inconsistenci
Externí odkaz:
http://arxiv.org/abs/2407.09303
Recent studies construct deblurred neural radiance fields (DeRF) using dozens of blurry images, which are not practical scenarios if only a limited number of blurry images are available. This paper focuses on constructing DeRF from sparse-view for mo
Externí odkaz:
http://arxiv.org/abs/2407.06613
Neural radiance fields (NeRFs) have received significant attention due to their high-quality novel view rendering ability, prompting research to address various real-world cases. One critical challenge is the camera motion blur caused by camera movem
Externí odkaz:
http://arxiv.org/abs/2407.03923
In speech separation, time-domain approaches have successfully replaced the time-frequency domain with latent sequence feature from a learnable encoder. Conventionally, the feature is separated into speaker-specific ones at the final stage of the net
Externí odkaz:
http://arxiv.org/abs/2406.05983
Neural radiance fields (NeRF) has attracted considerable attention for their exceptional ability in synthesizing novel views with high fidelity. However, the presence of motion blur, resulting from slight camera movements during extended shutter expo
Externí odkaz:
http://arxiv.org/abs/2403.07547