activity
20232026
most citedSet Features for Fine-grained Anomaly Detection

12 citations · 16 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Stuck on Shuffle: On Attribute-Object Binding in Vision-Language Models

Netanel Y. Tamir, Michael Green, Issar Tzachor +4

Retrieval is a fundamental task in multimodal systems: given an image or text query, the goal is to find the most relevant images or texts in a collection, often using a shared emb…

cs.CV2026

WarpHammer: Densifying Scene Warps with 3D Object Priors for Extreme View Synthesis

Michael Green, Gavriel Habib, Dvir Samuel +4

Projection-conditioned novel view synthesis (NVS) warps an explicit 3D reconstruction of the input view into the target camera and conditions a generator on the warped rendering. T…

cs.CV2026

VidMsg: A Benchmark for Implicit Message Inference in Short Videos

Issar Tzachor, Michael Green, Rami Ben-Ari

Understanding short online videos involves more than identifying visible objects and actions; video makers often include an underlying message or purpose in the clip. We introduce…

cs.CV2026

Retrieval-Augmented Gaussian Avatars: Improving Expression Generalization

Matan Levy, Gavriel Habib, Issar Tzachor +5

Template-free animatable head avatars can achieve high visual fidelity by learning expression-dependent facial deformation directly from a subject's capture, avoiding parametric fa…

cs.CV2026

VidVec: Unlocking Video MLLM Embeddings for Video-Text Retrieval

Issar Tzachor, Dvir Samuel, Rami Ben-Ari

Recent studies have adapted generative Multimodal Large Language Models (MLLMs) into embedding extractors for vision tasks, typically through fine-tuning to produce universal repre…

cs.CV2026

Fast Autoregressive Video Diffusion and World Models with Temporal Cache Compression and Sparse Attention

Dvir Samuel, Issar Tzachor, Matan Levy +3

Autoregressive video diffusion models enable streaming generation, opening the door to long-form synthesis, video world models, and interactive neural game engines. However, their…

cs.CV2025

Find your Needle: Small Object Image Retrieval via Multi-Object Attention Optimization

Michael Green, Matan Levy, Issar Tzachor +3

We address the challenge of Small Object Image Retrieval (SoIR), where the goal is to retrieve images containing a specific small object, in a cluttered scene. The key challenge in…

cs.CV2024★ 3 cited

EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition

Issar Tzachor, Boaz Lerner, Matan Levy +8

The task of Visual Place Recognition (VPR) is to predict the location of a query image from a database of geo-tagged images. Recent studies in VPR have highlighted the significant…

cs.SE2024

Reproducing, Extending, and Analyzing Naming Experiments

Rachel Alpern, Ido Lazer, Issar Tzachor +3

Naming is very important in software development, as names are often the only vehicle of meaning about what the code is intended to do. A recent study on how developers choose name…

cs.CV2023★ 1 cited

Set Features for Anomaly Detection

Niv Cohen, Issar Tzachor, Yedid Hoshen

This paper proposes to use set features for detecting anomalies in samples that consist of unusual combinations of normal elements. Many leading methods discover anomalies by detec…

cs.CV2023★ 12 cited

Set Features for Fine-grained Anomaly Detection

Niv Cohen, Issar Tzachor, Yedid Hoshen

Fine-grained anomaly detection has recently been dominated by segmentation based approaches. These approaches first classify each element of the sample (e.g., image patch) as norma…