I am a Ph.D student at Seoul National University, under the supervision of Prof. Nojun Kwak.
My research interests center around computer vision, with experience spanning across video rendering, 3D object detection, segmentation, and network pruning. My primary focus is on video generation & editing, aiming to push the boundaries of their applications in real-world scenarios.
There is a conflict among contextual embeddings in zero-shot T2I customization when varying the subject's pose. We resolve it by orthogonalization and attention swap.
We adopt motion personalization in video editing tasks, isolating the motion from a single source video and subsequently modifying the protagonist accordingly.
We advance dynamic pruning by employing refined gradients to update the pruned weights, enhancing both training stability and the model performance.
In video scene rendering, we reformulate neural radiance fields to additionally consider consistency fields, enabling more efficient and controllable scene manipulation.
We utilize the Gaussian Mixture Model (GMM) in the 3D object detection task to predict the distribution of 3D bounding boxes, eliminating the need for laborious, hand-crafted anchor design.
We delve into data augmentation in 3D object detection, leveraging sophisticated and rich structural information present in 3D labels.