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Found 11 papers, 5 papers with code
J-CRe3: A Japanese Conversation Dataset for Real-world Reference Resolution
Understanding expressions that refer to the physical world is crucial for such human-assisting systems in the real world, as robots that must perform actions that are expected by users.
A Gaze-grounded Visual Question Answering Dataset for Clarifying Ambiguous Japanese Questions
Such ambiguities in questions are often clarified by the contexts in conversational situations, such as joint attention with a user or user gaze information.
Multi-View Video-Based Learning: Leveraging Weak Labels for Frame-Level Perception
In this paper, we propose a novel learning framework, where the weak labels are first used to train a multi-view video-based base model, which is subsequently used for downstream frame-level perception tasks.
ManifoldNeRF: View-dependent Image Feature Supervision for Few-shot Neural Radiance Fields
DietNeRF is an extension of NeRF that aims to achieve this task from only a few images by introducing a new loss function for unknown viewpoints with no input images.
Small Object Detection for Birds with Swin Transformer
Object detection is the task of detecting objects in an image.
Ranked #4 on
Small Object Detection
on SOD4SB Public Test
(using extra training data)
MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results
Small Object Detection (SOD) is an important machine vision topic because (i) a variety of real-world applications require object detection for distant objects and (ii) SOD is a challenging task due to the noisy, blurred, and less-informative image appearances of small objects.
Ranked #2 on
Small Object Detection
on SOD4SB Public Test
(using extra training data)
DeePoint: Visual Pointing Recognition and Direction Estimation
The first is the introduction of a first-of-its-kind large-scale dataset for pointing recognition and direction estimation, which we refer to as the DP Dataset.
IPA-CLIP: Integrating Phonetic Priors into Vision and Language Pretraining
Furthermore, in some multimodal retrieval tasks, we confirm that the proposed pronunciation encoder enhances the performance of the text encoder and that the pronunciation encoder handles nonsense words in a more phonetic manner than the text encoder.
A Multimodal Sensor Fusion Framework Robust to Missing Modalities for Person Recognition
In the framework, a novel deep latent embedding framework, termed the AVTNet, is proposed to learn multiple latent embeddings.
SDOF-Tracker: Fast and Accurate Multiple Human Tracking by Skipped-Detection and Optical-Flow
To maintain the tracking accuracy, we introduce robust interest point selection within human regions and a tracking termination metric calculated by the distribution of the interest points.
Multiple Human Tracking using Multi-Cues including Primitive Action Features
The accurate human tracking result using PAF helps multi-frame-based action recognition.
