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Victor Sanchez

15 accepted papers

2026

Newton-coupled Dual-Teacher Semi-supervised Learning Framework

ICML 2026poster

Most semi-supervised learning frameworks rely on a single teacher that transfers zero-order supervision through pseudo-labels, constraining the student to imitate categorical outputs without perceiving the loss geometry. This design often leads to unstable optimization and limited generalization und…

Cited by 0SourceScholar
2025

LLplace: Embodied 3D Indoor Layout Synthesis Framework with Large Language Model

IROS 2025

Designing 3D indoor layouts is a crucial task with significant applications in embodied robot intelligence, virtual reality, and interior design. Existing methods for 3D layout design either rely on diffusion models, which utilize spatial relationship priors, or heavily leverage the inferential capa

Cited by 0SourceScholar
2025

OptiScene: LLM-driven Indoor Scene Layout Generation via Scaled Human-aligned Data Synthesis and Multi-Stage Preference Optimization

NeurIPS 2025poster

Automatic indoor layout generation has attracted increasing attention due to its potential in interior design, virtual environment construction, and embodied AI. Existing methods fall into two categories: prompt-driven approaches that leverage proprietary LLM services (e.g., GPT APIs), and learning-…

Cited by 0SourceScholar
2025

Semi-ViM: Bidirectional State Space Model for Mitigating Label Imbalance in Semi-Supervised Learning

ICCV 2025poster

Semi-supervised learning (SSL) is often hindered by learning biases when imbalanced datasets are used for training, which limits its effectiveness in real-world applications. In this paper, we propose Semi-ViM, a novel SSL framework based on Vision Mamba, a bidirectional state space model (SSM) that…

Cited by 0SourcePDFScholar
2022

Video Anomaly Detection via Prediction Network with Enhanced Spatio-Temporal Memory Exchange

ICASSP 2022accepted

Video anomaly detection is a challenging task because most anomalies are scarce and non-deterministic. Many approaches investigate the reconstruction difference between normal and abnormal patterns, but neglect that anomalies do not necessarily correspond to large reconstruction errors. To address t…

Cited by 0SourceScholar
2019

Learning Temporal Information from Spatial Information Using CapsNets for Human Action Recognition

ICASSP 2019accepted

Capsule Networks (CapsNets) are recently introduced to overcome some of the shortcomings of traditional Convolutional Neural Networks (CNNs). CapsNets replace neurons in CNNs with vectors to retain spatial relationships among the features. In this paper, we propose a CapsNet architecture that employ…

Cited by 0SourceScholar
2017

Patch-based segmentation of overlapping cervical cells using active contour with local edge information

ICASSP 2017accepted

The Pap test is a manual screening procedure that is used to detect the precursor lesions of cervical cancer by analyzing changes in nuclei and cytoplasms of cervical cells. Due to the sensitivity of the Pap test to intra- and inter-observer variability, automating the procedure using digital image…

Cited by 0SourceScholar
2016

Fast lossless compression of whole slide pathology images using HEVC intra-prediction

ICASSP 2016accepted

The lossless compression of Whole Slide pathology Images (WSIs) using HEVC is investigated in this paper. Recently proposed intra-prediction algorithms based on differential pulse-code modulation (DPCM) and edge prediction provide significant bitrate improvements for a wide range of natural and scre…

Cited by 0SourceScholar
2015

Rate control for lossless region of interest coding in HEVC intra-coding with applications to digital pathology images

ICASSP 2015accepted

This paper proposes a rate control algorithm for lossless region of interest (RoI) coding in HEVC intra-coding. The algorithm is developed for digital pathology images and allows for random access to the data. Based on an input RoI mask, the algorithm first encodes the RoI losslessly. According to t…

Cited by 0SourceScholar