22 citations · 86 across the 24 of their papers we have counts for
24 papers
Stabilizing Camera-Controlled Novel View Synthesis at Inference Time
Prajwal Singh, Arjun Badola, Seema Kumari +2
Training-free, camera-controlled novel view synthesis from a single image using pre-trained video diffusion models often becomes unstable under large camera motion and long generat…
Inverse Rendering of Translucent Objects using Physical and Neural Renderers
Chenhao Li, Trung Thanh Ngo, Hajime Nagahara
In this work, we propose an inverse rendering model that estimates 3D shape, spatially-varying reflectance, homogeneous subsurface scattering parameters, and an environment illumin…
Human-Imperceptible Identification with Learnable Lensless Imaging
Thuong Nguyen Canh, Trung Thanh Ngo, Hajime Nagahara
Lensless imaging protects visual privacy by capturing heavily blurred images that are imperceptible for humans to recognize the subject but contain enough information for machines…
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers
Hugo Lemarchant, Liangzi Li, Yiming Qian +2
Vision Transformers (ViTs) are becoming a very popular paradigm for vision tasks as they achieve state-of-the-art performance on image classification. However, although early works…
Contrastive Losses Are Natural Criteria for Unsupervised Video Summarization
Zongshang Pang, Yuta Nakashima, Mayu Otani +1
Video summarization aims to select the most informative subset of frames in a video to facilitate efficient video browsing. Unsupervised methods usually rely on heuristic training…
A General Scattering Phase Function for Inverse Rendering
Thanh-Trung Ngo, Hajime Nagahara
We tackle the problem of modeling light scattering in homogeneous translucent material and estimating its scattering parameters. A scattering phase function is one of such paramete…
Learning More May Not Be Better: Knowledge Transferability in Vision and Language Tasks
Tianwei Chen, Noa Garcia, Mayu Otani +3
Is more data always better to train vision-and-language models? We study knowledge transferability in multi-modal tasks. The current tendency in machine learning is to assume that…
Privacy-Preserving Action Recognition via Motion Difference Quantization
Sudhakar Kumawat, Hajime Nagahara
The widespread use of smart computer vision systems in our personal spaces has led to an increased consciousness about the privacy and security risks that these systems pose. On th…
Acquiring a Dynamic Light Field through a Single-Shot Coded Image
Ryoya Mizuno, Keita Takahashi, Michitaka Yoshida +3
We propose a method for compressively acquiring a dynamic light field (a 5-D volume) through a single-shot coded image (a 2-D measurement). We designed an imaging model that synchr…
Built Year Prediction from Buddha Face with Heterogeneous Labels
Yiming Qian, Cheikh Brahim El Vaigh, Yuta Nakashima +3
Buddha statues are a part of human culture, especially of the Asia area, and they have been alongside human civilisation for more than 2,000 years. As history goes by, due to wars,…
GCNBoost: Artwork Classification by Label Propagation through a Knowledge Graph
Cheikh Brahim El Vaigh, Noa Garcia, Benjamin Renoust +3
The rise of digitization of cultural documents offers large-scale contents, opening the road for development of AI systems in order to preserve, search, and deliver cultural herita…
Development of a Vertex Finding Algorithm using Recurrent Neural Network
Kiichi Goto, Taikan Suehara, Tamaki Yoshioka +5
Deep learning is a rapidly-evolving technology with possibility to significantly improve physics reach of collider experiments. In this study we developed a novel algorithm of vert…
Match Them Up: Visually Explainable Few-shot Image Classification
Bowen Wang, Liangzhi Li, Manisha Verma +3
Few-shot learning (FSL) approaches are usually based on an assumption that the pre-trained knowledge can be obtained from base (seen) categories and can be well transferred to nove…
Automated Grading System of Retinal Arterio-venous Crossing Patterns: A Deep Learning Approach Replicating Ophthalmologist's Diagnostic Process of Arteriolosclerosis
Liangzhi Li, Manisha Verma, Bowen Wang +3
The status of retinal arteriovenous crossing is of great significance for clinical evaluation of arteriolosclerosis and systemic hypertension. As an ophthalmology diagnostic criter…
Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation
Bowen Wang, Liangzhi Li, Yuta Nakashima +3
Semantic video segmentation is a key challenge for various applications. This paper presents a new model named Noisy-LSTM, which is trainable in an end-to-end manner, with convolut…
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition
Liangzhi Li, Bowen Wang, Manisha Verma +3
Explainable artificial intelligence has been gaining attention in the past few years. However, most existing methods are based on gradients or intermediate features, which are not…
Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing
Liangzhi Li, Manisha Verma, Yuta Nakashima +2
Retinal imaging serves as a valuable tool for diagnosis of various diseases. However, reading retinal images is a difficult and time-consuming task even for experienced specialists…
5D Light Field Synthesis from a Monocular Video
Kyuho Bae, Andre Ivan, Hajime Nagahara +1
Commercially available light field cameras have difficulty in capturing 5D (4D + time) light field videos. They can only capture still light filed images or are excessively expensi…
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
Liangzhi Li, Manisha Verma, Yuta Nakashima +2
Retinal vessel segmentation is of great interest for diagnosis of retinal vascular diseases. To further improve the performance of vessel segmentation, we propose IterNet, a new mo…
Historical and Modern Features for Buddha Statue Classification
Benjamin Renoust, Matheus Oliveira Franca, Jacob Chan +7
While Buddhism has spread along the Silk Roads, many pieces of art have been displaced. Only a few experts may identify these works, subjectively to their experience. The construct…
BUDA.ART: A Multimodal Content-Based Analysis and Retrieval System for Buddha Statues
Benjamin Renoust, Matheus Oliveira Franca, Jacob Chan +6
We introduce BUDA.ART, a system designed to assist researchers in Art History, to explore and analyze an archive of pictures of Buddha statues. The system combines different CBIR a…
Using Natural Language Processing to Develop an Automated Orthodontic Diagnostic System
Tomoyuki Kajiwara, Chihiro Tanikawa, Yuujin Shimizu +3
We work on the task of automatically designing a treatment plan from the findings included in the medical certificate written by the dentist. To develop an artificial intelligence…
TransCut: Transparent Object Segmentation from a Light-Field Image
Yichao Xu, Hajime Nagahara, Atsushi Shimada +1
The segmentation of transparent objects can be very useful in computer vision applications. However, because they borrow texture from their background and have a similar appearance…
Mobile Camera Array Calibration for Light Field Acquisition
Yichao Xu, Kazuki Maeno, Hajime Nagahara +1
The light field camera is useful for computer graphics and vision applications. Calibration is an essential step for these applications. After calibration, we can rectify the captu…